4
Already Validated
9
Active Testing (2026)
13
Near-Term (2-5 Years)
9
Long-Term (10+ Years)

About This Page

This page tracks all testable predictions from the COSMIC Framework and related preprints. Predictions are documented with specific dates before experimental testing to establish scientific priority. Updates reflect testing progress, results, and new predictions.

Validation Strategy: We employ a two-phase approach where Phase 1 (2026-2027) validates framework principles through information encoding systems, followed by Phase 2 (2027-2029) applying validated principles to sensory augmentation. This staged validation reduces risk and accelerates development.

Current Status: 4 predictions validated (4.2Οƒ statistical significance), 9 predictions in active testing (2026), 37 total predictions spanning cognitive augmentation, cosmology, quantum mechanics, consciousness research, and sleep neuroscience.

🧠 Cognitive Augmentation Preprints (2026-2029)

Predictions from "AI-Mediated Cognitive Extension" and "Optimal Information Encoding for Cognitive Augmentation" preprints. Published January 31, 2026.

Phase 1: Information Encoding Validation (2026-2027)

Status: Development beginning Q1 2026, testing starts Q2 2026

Purpose: Validate framework principles (working memory optimization, AI-mediated compression, neuroplastic adaptation) in accessible domain before investing in sensory augmentation hardware.

Preprint: Optimal Information Encoding for Cognitive Augmentation

1.1 Working Memory Chunk Limit (Information Encoding)

TESTING Q2 2026
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: April 2026 πŸ“Š Results Expected: July 2026

Hypothesis: Text presentation requiring more than 2-3 simultaneous working memory chunks will degrade comprehension by at least 15%.

Test Method

Dual-task paradigm with variable text complexity. Users perform reading comprehension tasks while working memory load is systematically varied. Comprehension accuracy and cognitive load measured across conditions.

Success Criteria

Comprehension degrades by β‰₯15% when text complexity exceeds 2-3 working memory chunks, measured at p<0.05 significance level with effect size dβ‰₯0.5.

Framework Implication

If validated, confirms working memory as fundamental bottleneck for information processing, supporting the crystallized intelligence trap model from "The Speed of Novelty."

1.2 Adaptive Compression Benefits (Information Encoding)

TESTING Q2 2026
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: May 2026 πŸ“Š Results Expected: August 2026

Hypothesis: AI-adjusted text density will improve reading speed by 2-3Γ— for narrative content and 10-20Γ— for technical content.

Test Method

Controlled reading tasks with expertise-matched groups. Compare reading speed and comprehension between traditional static text and AI-adaptive presentation. Measure across content types (narrative vs. technical) and expertise levels.

Quantitative Specifications

Narrative text (novels, news): 200-400 wpm baseline β†’ 400-800 wpm adaptive (2-3Γ— improvement)

Technical text (papers, textbooks): 50-150 wpm baseline β†’ 500-1500 wpm adaptive (10-20Γ— improvement)

Framework Implication

If validated, demonstrates that AI can handle crystallized intelligence (definition lookup, context retrieval) while preserving working memory for comprehension.

1.3 Knowledge Retention Enhancement (Information Encoding)

TESTING Q2 2026
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: April 2026 πŸ“Š Initial Results: June 2026 (1-month)

Hypothesis: Knowledge graph storage produces 50-70% better retention at 1 month compared to traditional document-based learning.

Test Method

Crossover design where users learn new material using both methods. Surprise retention tests at 1 week, 1 month, and 6 months. Control for study time, topic difficulty, and user variables.

Quantitative Specifications

1-week retention: 40-60% traditional β†’ 70-85% knowledge graph

1-month retention: 20-35% traditional β†’ 50-70% knowledge graph

6-month retention: 10-20% traditional β†’ 35-55% knowledge graph

Mechanism

Semantic connections in knowledge graphs reinforce memory through retrieval practice built into navigation. Information connected to existing knowledge structures shows superior retention.

1.4 Expertise Interaction Effect (Information Encoding)

TESTING Q2-Q3 2026
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: May 2026 πŸ“Š Results Expected: September 2026

Hypothesis: Intermediate users show largest benefit (80-200% improvement) from adaptive encoding, following an inverted-U curve.

Test Method

Cross-sectional study across expertise levels (novice: <2 years, intermediate: 2-8 years, expert: >8 years). Measure performance improvement and adaptation time for each group.

Predicted Performance Improvements

Novices (knowledge limitation): 30-60% improvement, moderate cognitive load

Intermediate users (optimal zone): 80-200% improvement, low cognitive load

Experts (adaptation difficulty): 40-120% improvement, initially high cognitive load declining with training

Framework Implication

If validated, supports crystallized intelligence trap model. Experts struggle with novel information because accumulated knowledge creates inflexibility. Intermediate users benefit most as they have sufficient expertise but aren't yet trapped.

Phase 2: Sensory Augmentation (2027-2029)

Status: Awaiting Phase 1 validation, planned start Q2 2027

Prerequisite: At least 3 of 4 Phase 1 predictions must validate at p<0.05 before proceeding

Preprint: AI-Mediated Cognitive Extension: Engineering Solutions to Substrate Constraints

2.1 Working Memory Chunk Limit (Sensory Augmentation)

Q4 2027
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: Q4 2027 πŸ“Š Results Expected: Q1 2028

Hypothesis: Augmented sensory information exceeding 2-3 chunks degrades primary task performance by at least 15%.

Test Method

Dual-task paradigm with thermal and chemical sensing. Users perform primary tasks (medical diagnosis, navigation, threat detection) while receiving augmented sensory information. Systematically vary augmentation complexity.

Success Criteria

Performance improvement when augmented information ≀2 chunks. Performance degradation β‰₯15% when augmented information β‰₯3 chunks. Sharp performance cliff at threshold.

Leveraged Parameters from Phase 1

Uses exact working memory threshold measured in Phase 1 (predicted 2-3 chunks) to optimize augmentation design. Compression algorithms proven effective in Phase 1 applied to sensory domain.

2.2 Neuroplastic Adaptation Timeline

Q4 2027 - Q3 2028
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: Q4 2027 πŸ“Š Complete: Q3 2028 (12-month study)

Hypothesis: Novel sense integration follows 3-phase pattern: conscious translation (weeks 1-2), automatization (weeks 3-6), perceptual integration (weeks 6-12).

Test Method

Longitudinal study with thermal perception augmentation. Track same users over 90 days. Measure working memory load (dual-task), performance (task-specific metrics), subjective experience (structured interviews), and neural activation (fMRI/EEG) at regular intervals.

Predicted Three-Phase Pattern

Phase 1 (Days 1-14): Working memory load 2-3 chunks, performance improvement 0-20%, conscious "interpreting signals," prefrontal cortex activation

Phase 2 (Days 15-45): Working memory load 1-2 chunks declining, performance improvement 20-60%, "getting easier," declining prefrontal activation

Phase 3 (Days 45-90): Working memory load <1 chunk, performance improvement 60-150%, "feels like another sense," stable multimodal integration

Framework Implication

If validated, demonstrates cross-modal plasticity can incorporate artificial senses using same mechanisms as natural senses, with timeline determined by information-theoretic properties of the interface.

2.3 Modality Effectiveness Tiers

Q1-Q3 2028
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing: Q1-Q3 2028 πŸ“Š Results Expected: Q4 2028

Hypothesis: Augmentation effectiveness follows clear tiers: Spatial-motor (100-200%) > Pattern recognition (60-150%) > Temporal pattern (30-100%) > Abstract overlay (0-50%).

Test Method

Cross-sectional comparison after 90-day training across modality types. Control for task difficulty, user expertise, and interface quality. Measure both performance improvement and cognitive load.

Ranked Effectiveness (Best to Worst)

Tier 1 (100-200%): Spatial-motor augmentation (magnetoreception for navigation, ultrasonic echolocation, infrared thermal mapping). Maps naturally to existing spatial perception.

Tier 2 (60-150%): Pattern recognition augmentation (chemical threat detection, medical diagnostic sensing). Requires domain expertise but provides decision-relevant patterns.

Tier 3 (30-100%): Temporal pattern augmentation (infrasonic/ultrasonic hearing, electromagnetic field variation). Harder to compress and integrate with spatial behavior.

Tier 4 (0-50%): Abstract information overlay (text alerts, numerical data, symbolic information). Requires cognitive interpretation, consumes working memory.

Framework Implication

If validated, confirms perceptual integration (low working memory load) produces superior outcomes vs. cognitive interpretation (high working memory load), even when providing same underlying information.

2.4 Environmental Psychology Transformation

Q4 2027 - Q2 2028
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing Begins: Q4 2027 πŸ“Š 6-Month Results: Q2 2028

Hypothesis: Augmented environmental perception (atmospheric chemistry, thermal patterns, electromagnetic fields) increases ecological connectedness by 40-60% and pro-environmental behavior by 50-80%.

Test Method

Longitudinal psychological assessment over 6 months. Compare augmentation users to control population. Measure Connectedness to Nature Scale (CNS), New Environmental Paradigm (NEP), behavioral tracking, and qualitative phenomenology reports.

Quantitative Metrics

Connectedness to Nature Scale (CNS): +40-60% after 6 months

Environmental concern (NEP): +30-50%

Pro-environmental behavior frequency: +50-80%

Self-reported "direct perception of environmental connection": >70% of augmented users

Mechanism

Direct perceptual experience of environmental information exchange creates phenomenological understanding that abstract knowledge cannot provide. Perceiving your breath affecting atmospheric chemistry transforms environmental connection from intellectual concept to lived experience.

Climate Impact

If validated, suggests augmented perception could accelerate pro-environmental behavioral change more effectively than education campaigns, potentially contributing to climate crisis response.

2.5 Substrate Perception (Exploratory)

Q3-Q4 2028
πŸ“… Documented: January 31, 2026 πŸ”¬ Testing: Q3-Q4 2028 (requires advanced system) ⚠️ Speculative, high impact if validated

Hypothesis: Minimal-filtering augmentation configuration produces phenomenology similar to DMT experiences (r>0.6 correlation), suggesting access to substrate-level information structure.

Theoretical Basis

If DMT experiences represent reduced filtering of substrate-level information (underlying information-theoretic structure of physical reality), we should reproduce aspects through controlled, selective reduction of perceptual filtering.

Test Configuration

Augmentation system presenting: high-frequency electromagnetic field variations (microwave to IR), quantum vacuum fluctuation patterns (if detectable), rapid temporal variation in local information density, and multi-scale spatial pattern correlations.

Information compressed but minimally filtered, preserving substrate detail while keeping within working memory constraints through selective attention.

Predicted Phenomenology

Geometric patterns not in normal visual field, sensation of "higher-dimensional" structure, rapid information transmission feeling, similarity to DMT-like geometry, sense of perceiving "underlying structure" of reality.

Quantitative Metrics

Correlation with DMT phenomenology questionnaires: r > 0.6

Geometric pattern perception increase: >300% vs normal augmentation

Subjects without prior psychedelic experience report geometry similar to experienced DMT users

Framework Implication

If validated: Strong evidence that DMT experiences represent genuine substrate-level information perception, same information is accessible through technological means, COSMIC Framework's information-theoretic substrate model describes real features of physical reality.

If not validated: Suggests DMT phenomenology arises from neural dynamics rather than substrate perception, weakening but not disproving substrate perception hypothesis.

Risk/Uncertainty

This prediction is inherently more speculative than others. Failure wouldn't disprove broader framework, but success would provide remarkable support. Requires sophisticated augmentation systems with high temporal and spatial resolution.

βœ“ Validated Predictions (4)

Predictions confirmed by experimental observation - 100% success rate (4.2Οƒ statistical significance)

Dark Energy Equation of State Evolution

βœ“ VALIDATED
πŸ“… Documented: January 29, 2024 (Notarized US & Thailand) βœ… Validated: January 7, 2025 (DESI, 3.9Οƒ)

Specific Claim: Dark energy is not constant (Ξ›) but evolves over cosmic time with equation of state w(z) = wβ‚€ + wₐ·z/(1+z), where wβ‚€ β‰ˆ -0.95 and wₐ β‰ˆ -0.3.

w(z) = wβ‚€ + wₐ Β· z/(1+z)
with wβ‚€ β‰ˆ -1 and |wₐ| > 0.01

Testing Method

  • Type Ia supernova observations across redshift range
  • Baryon acoustic oscillations in galaxy surveys
  • Weak gravitational lensing
  • Integrated Sachs-Wolfe effect in CMB

Validation Results

DESI reported 3.9Οƒ evidence for evolving dark energy with wβ‚€ = -0.94 Β± 0.09 and wₐ = -0.27 Β± 0.15, directly confirming framework predictions within 1Οƒ.

Falsification Criterion

If future surveys with Ξ”w β‰ˆ 0.005 precision find w = -1.000 Β± 0.005 at all redshifts, the prediction is falsified.

Quantum Error Correction Exponential Scaling

βœ“ VALIDATED
πŸ“… Documented: August 12, 2024 βœ… Validated: December 9, 2024 (Google Willow)

Specific Claim: Quantum error correction would follow information optimization principles, resulting in exponential error suppression as qubit count increases, with error rates decreasing by half with each additional qubit layer when properly optimized.

Testing Method

Surface code quantum error correction with increasing grid sizes (3Γ—3 β†’ 5Γ—5 β†’ 7Γ—7 qubits), measuring error rates at each scale.

Validation Results

Google Quantum AI's Willow chip demonstrated exponential suppression of errors, achieving below-threshold performance. Each grid size increase halved the error rate, exactly matching framework predictions.

Scientific Impact

First demonstration that information optimization principles apply beyond cosmology, validating framework universality across quantum and cosmic domains.

Enhanced Early Galaxy Formation

βœ“ VALIDATED
πŸ“… Documented: March 5, 2024 βœ… Validated: 2023-2024 (JWST)

Specific Claim: Early universe galaxies (z=10-15) would be significantly more massive than Ξ›-CDM models predict, with ~100+ massive galaxies at these redshifts showing 4-5x mass enhancement.

A(z) β‰ˆ 2-2.5 at z=10
M_observed β‰ˆ M_standard Γ— (4-5)

Testing Method

JWST deep field observations with multi-band imaging and spectroscopic confirmations at z > 10.

Validation Results

Over 100 massive galaxy candidates discovered at z=10-15, with masses 4-5x greater than Ξ›-CDM predictions. Enhancement factor matches framework's A(z) predictions.

Enhanced Thermal Energy in Early Universe Clusters

βœ“ VALIDATED
πŸ“… Documented: March 5, 2024 βœ… Validated: January 7, 2026 (ALMA SPT2349-56, Published in Nature)

Specific Claim: Early universe clusters would exhibit enhanced energy states due to information optimization efficiency at high redshift, manifesting as dramatically higher thermal energy than gravitational models predict, with enhancement factors matching the framework's A(z) predictions.

E(z) ∝ (1+z)^1.2
Predicted enhancement: A(z) β‰ˆ 4-5 at z=4-10

Validation Results (January 7, 2026)

Discovery: ALMA observations of protocluster SPT2349-56 at redshift z=4.3 (1.4 billion years after Big Bang) revealed superheated intracluster gas with thermal energy ~10⁢¹ erg.

Enhancement Factor: Gas temperatures exceed 10 million Kelvinβ€”approximately 10 times hotter than gravity alone should produce, and at least 5 times hotter than Ξ›-CDM predictions.

Additional Confirmation: Star formation rate 5,000x faster than Milky Way, with 30+ galaxies packed into 500,000 light-year region.

Quote from Research Team: "We didn't expect to see such a hot cluster atmosphere so early in cosmic history... this gas is at least five times hotter than predicted, and even hotter than what we find in many present-day clusters."

Scientific Impact

Convergent Validation: This represents an entirely independent observable (thermodynamics) showing the same ~5-10x enhancement as galaxy masses at similar redshifts, strengthening convergent evidence for the information-first framework.

Challenge to Standard Model: Current cosmological models predict gradual heating over billions of years. This discovery forces reconsideration of galaxy cluster formation timelines and mechanisms.

Framework Consistency: The enhanced thermal energy matches framework predictions that higher information processing efficiency at early times produces accelerated structure formation and energy concentration.

Publication Details

Zhou, D. et al. (2026). "Sunyaev-Zeldovich detection of hot intracluster gas at redshift 4.3." Nature, published online January 5, 2026. DOI: 10.1038/s41586-025-09901-3

Near-Term Predictions (1-5 Years)

Testable with current or imminent technology (12 predictions)

Information-Efficiency Hubble Parameter Evolution

1-3 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: 2025-2028

Specific Claim: The Hubble tension arises from information density evolution affecting expansion rate measurements. Local measurements (zβ‰ˆ0) differ from CMB (zβ‰ˆ1100) due to accumulated information.

H(z) = Hβ‚€ Γ— [1 + Ξ» Γ— (E(z)/Eβ‚€ - 1)]
where Ξ» β‰ˆ 10⁻⁡

Testable Predictions

  • H(z) measurements at z=0.5-2.0 should show systematic evolution
  • Tension should correlate with information density proxies
  • Standard siren measurements should match framework predictions

Testing Facilities

James Webb Space Telescope, Euclid Mission, LIGO/Virgo gravitational wave observations, Roman Space Telescope

Falsification Criterion

If intermediate-z measurements match either local or CMB value exactly with no systematic evolution, prediction is falsified.

Redshift-Dependent Structure Formation Enhancement

2-5 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: 2026-2030

Specific Claim: Structure formation efficiency shows systematic enhancement with redshift following A(z) ∝ (1+z)^Ξ² where Ξ² β‰ˆ 0.4, creating transition epoch at z β‰ˆ 6-8.

Observable Predictions

  • Galaxy mass functions at z=6-10 exceed Ξ›-CDM by factor 2-3
  • Halo concentrations higher at high-z than standard models predict
  • Transition epoch visible in multiple independent observables

Testing Method

Continued JWST observations, Extremely Large Telescope first light, Nancy Grace Roman wide-field surveys, correlation function measurements

Multi-Scale Cosmic Axis Alignment

1-5 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: Ongoing analysis

Specific Claim: Multiple independent phenomena should align with same cosmic axis if spacetime emerged from substrate phase transition: CMB anomalies, galaxy spin directions, void alignments, and large-scale structure orientation.

Axis direction: (l, b) β‰ˆ (210Β°, -20Β°) Β± 30Β°

Current Evidence

  • CMB hemispherical asymmetry: (213Β°, -21Β°)
  • Axis of evil alignment: (210Β°, -60Β°)
  • Galaxy spin correlations (Shamir 2022): consistent direction
  • Statistical significance: 3Οƒ, Bayes factor 0.0041 against isotropy

Upcoming Tests

Euclid Mission analysis, additional large-scale structure surveys, void alignment measurements, cross-correlation between independent datasets

Falsification Criterion

If anomalies are uncorrelated or disappear with better foreground removal, substrate interpretation is falsified.

Dark Energy-Matter Density Cross-Correlation

3-5 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: 2027-2030

Specific Claim: If dark energy emerges from information processing, fluctuations in dark energy density should correlate with matter density fluctuations.

Correlation coefficient: ρ(δw, δρ) > 0.1

Testing Method

  • Cross-correlation of weak lensing with galaxy distribution
  • Void analysis (lowest information density regions)
  • Statistical analysis of cosmic structure

Required Data

Euclid weak lensing surveys, LSST galaxy catalogs, Roman Space Telescope observations

Falsification Criterion

If correlation ρ < 0.01 or negative correlation found, prediction is falsified.

Measurable Consciousness Information Processing Energy

2-5 YEARS
πŸ“… Documented: March-August 2024 πŸ”¬ Timeline: Laboratory measurements

Specific Claim: Conscious thought requires measurable energy dissipation following Landauer's principle, with single thoughts dissipating ~10⁻¹⁸ to 10⁻¹⁡ J.

E_thought = n_bits Γ— kT ln(2) Γ— Ξ·_neural
where Ξ·_neural β‰ˆ 10⁻⁢

Testing Protocol

  • High-precision calorimetry during controlled cognitive tasks
  • Measure heat dissipation beyond basal metabolic rate
  • Compare different consciousness states (meditation, focused thought, sleep)
  • Correlation with neural activity patterns

Required Sensitivity

Calorimetry with ~10⁻¹⁸ J resolution, currently achievable with state-of-the-art techniques

Sleep-Dependent Information Erasure and Thermodynamic Signatures

1-3 YEARS
πŸ“… Documented: January 31, 2026 πŸ”¬ Timeline: 2026-2028

Framework Connection: Existing sleep research has extensively documented synaptic downscaling during sleep but describes it as "homeostatic" without explaining the fundamental physical necessity. The COSMIC Framework reinterprets this as thermodynamically mandatory information erasure following Landauer's principle.

Key Insight: Current theories describe WHAT happens (synaptic downscaling) and WHAT the benefit is (preventing saturation), but not WHY it's physically necessary. The framework explains: you cannot continue processing new information without erasing old information, and information erasure must dissipate measurable heat.

πŸ”¬ Extensive Existing Research Foundation

This prediction leverages decades of rigorous sleep research:

  • Global Synaptic Downscaling: Contact areas between cortical axon terminals and dendritic spines globally reduce during sleep, with measurable decreases in synaptic AMPA receptor levels and synaptic strength (Nature Neuroscience 2019, PMC 2025)
  • Stage-Specific Mechanisms: NREM sleep selectively downscales highly active neurons; REM sleep induces broader network-wide synaptic weakening (BMB Reports 2025)
  • Memory Consolidation Through Replay: Hippocampal replay during slow-wave sleep drives transformation and integration of representations into neocortical networks (Nature Neuroscience 2019)
  • REM Refinement Function: REM sleep increases signal-to-noise ratio, chiseling away superfluous material while leveling activity across representations (SLEEP Advances 2025)
  • Homeostatic Function: Sleep prevents saturation and enhances capacity to integrate new information the following day (PMC 2021, Science Advances 2024)

The framework provides the missing fundamental explanation: these processes are thermodynamically required for continued information processing, not merely evolved optimizations.

Prediction 9B.1: Thermodynamic Heat Signature During Sleep

Hypothesis: Information erasure during sleep must dissipate measurable heat according to Landauer's principle: Ξ”E β‰₯ kT ln(2) per bit erased.

Specific Prediction: Heat dissipation during NREM sleep will correlate quantitatively with degree of synaptic downscaling, with signature distinct from baseline metabolic heat.

The "Symphony of Erasure":

While individual bit erasures (~10⁻²¹ J) are too small to detect in biological noise, synchronized information erasure across billions of neurons during sleep creates measurable thermodynamic signals:

  • Synaptic downscaling (NREM): ~10ΒΉΒ² synapses modified per night
  • Network-wide weakening (REM): Broader but less dramatic changes
  • Molecular markers: Measurable protein synthesis and gene expression changes

Testing Method:

  • High-precision calorimetry during controlled sleep studies
  • Simultaneous EEG monitoring to identify sleep stages
  • Molecular markers of synaptic downscaling (AMPA receptor levels, spine density)
  • Correlation analysis: heat dissipation vs. downscaling magnitude

Success Criteria: Significant correlation (p < 0.01) between heat dissipation and molecular markers of downscaling, with thermal signature distinguishable from baseline metabolism.

Prediction 9B.2: Stage-Specific Thermodynamic Signatures

Hypothesis: Different sleep stages show distinct thermodynamic profiles reflecting their different information processing functions.

Predicted Pattern:

  • NREM Sleep: Highest heat dissipation due to massive synaptic downscaling and selective erasure of highly active neurons
  • REM Sleep: Moderate heat dissipation from network-wide refinement and optimization
  • Deep Sleep (SWS): Maximum erasure with characteristic slow oscillations facilitating synchronized downscaling
  • Light Sleep: Minimal erasure, primarily transition state

Testing Method:

  • Continuous high-precision calorimetry throughout full sleep cycles
  • EEG/polysomnography for precise stage identification
  • Multiple subjects (nβ‰₯30) across multiple nights
  • Statistical analysis of thermal patterns vs. sleep architecture

Success Criteria: Distinguishable thermal signatures for each sleep stage with NREM > REM > Light sleep in heat dissipation, significant at p < 0.001.

Prediction 9B.3: Learning Load Predicts Erasure Magnitude

Hypothesis: Amount of information encoding during waking hours predicts magnitude of information erasure during subsequent sleep.

Specific Prediction: Subjects performing intensive learning tasks during the day will show:

  • Greater synaptic downscaling during sleep
  • Higher heat dissipation during NREM sleep
  • Longer duration of deep sleep stages
  • Quantitative correlation between learning intensity and erasure magnitude

Testing Protocol:

  • Experimental Days: Controlled learning tasks (variable intensity)
  • Control Days: Minimal new information exposure
  • Measurements: Learning trials quantified, sleep calorimetry, molecular markers
  • Analysis: Regression analysis of learning load vs. erasure metrics

Success Criteria: Significant positive correlation (r > 0.5, p < 0.01) between daytime learning quantification and nighttime erasure measurements.

Prediction 9B.4: Sleep Deprivation Shows Thermodynamic Accumulation

Hypothesis: Sleep deprivation creates accumulating thermodynamic stress as information processing continues without mandatory erasure cycles.

Predicted Effects:

  • Increasing metabolic cost per cognitive operation over days without sleep
  • Declining information processing efficiency (measurable via cognitive tasks)
  • Accumulated "erasure debt" requiring extended sleep for recovery
  • Recovery sleep shows elevated heat dissipation proportional to deprivation duration

Testing Method:

  • Controlled sleep deprivation protocol (24-72 hours)
  • Cognitive performance testing at regular intervals
  • Metabolic efficiency measurements (energy cost per task completed)
  • Recovery sleep monitoring with full calorimetry
  • Molecular markers of accumulated stress

Success Criteria:

  • Measurable decline in metabolic efficiency (p < 0.01)
  • Recovery sleep shows proportionally elevated heat dissipation
  • Cognitive performance decline correlates with thermodynamic metrics

Why This Validates the Framework

Current Sleep Research Theories:

  • Synaptic Homeostasis Hypothesis: Says downscaling maintains balance, but doesn't explain WHY balance is physically required
  • Active Systems Consolidation: Says replay transfers memories, but doesn't explain WHY transfer is necessary
  • Dual Process Hypothesis: Says NREM and REM serve different functions, but doesn't explain WHY both are required

COSMIC Framework Explanation:

Sleep is not an evolved optimizationβ€”it's the biological implementation of thermodynamically mandatory information erasure. The "saturation" current theories prevent isn't a memory capacity problem; it's hitting fundamental information-theoretic limits. You physically CANNOT continue processing information without periodic erasure.

Validation Pathway:

  • Takes well-established empirical findings (decades of sleep research)
  • Provides deeper, more fundamental explanation based on information physics
  • Makes testable quantitative predictions about thermodynamic signatures
  • Connects multiple independent observations through unified mechanism

Implementation Timeline

Phase 1 (2026):

  • Literature synthesis and protocol design
  • Equipment calibration and baseline measurements
  • Pilot studies with small sample (n=5-10)

Phase 2 (2027):

  • Full-scale testing (n=30-50 subjects)
  • Multiple nights per subject across conditions
  • Molecular marker correlation analysis
  • Statistical analysis and preliminary results

Phase 3 (2028):

  • Replication studies
  • Sleep deprivation protocols
  • Learning load manipulation experiments
  • Publication and independent validation

Required Resources

Equipment:

  • High-precision calorimetry (~10⁻¹⁸ J resolution)
  • Full polysomnography (EEG, EOG, EMG)
  • Molecular assay capabilities (AMPA receptor quantification, spine imaging)
  • Controlled sleep environment

Collaboration Partners:

  • Sleep research laboratories
  • Neuroscience departments with molecular capabilities
  • Precision measurement physics groups
  • Statistical analysis expertise

Estimated Budget: $500K-$1M over 3 years (significantly less than many predictions due to leveraging existing sleep research infrastructure)

Why This Is Uniquely Valuable

  • Massive Existing Data: Decades of rigorous, reproducible sleep research provides foundation
  • Less Controversial: Everyone sleeps; well-accepted phenomenon in mainstream neuroscience
  • Clear Mechanistic Predictions: Quantitative, falsifiable predictions about thermodynamic signatures
  • Practical Applications: Understanding sleep at fundamental level enables optimization
  • Validates Core Framework: Demonstrates information erasure is thermodynamically mandatory, not evolved optimization
  • Bridges Disciplines: Connects neuroscience, thermodynamics, information theory, and sleep medicine

Information-Optimized Quantum Coherence

2-4 YEARS
πŸ“… Documented: March-August 2024 πŸ”¬ Timeline: Laboratory quantum experiments

Specific Claim: Quantum systems with information-optimized geometries (e.g., Ο€-optimized circular configurations) should show enhanced coherence times beyond conventional predictions.

Testing Method

  • Compare identical quantum systems in different geometric configurations
  • Circular vs. square vs. hexagonal arrangements
  • Measure coherence time Tβ‚‚, gate fidelity, entanglement generation rate

Expected Results

Circular configurations show 0.1-1% enhanced performance. Enhancement scales with geometric Ο€-content.

Falsification

If no special enhancement for Ο€-optimized configurations beyond known symmetry effects, prediction is falsified.

Information Processing at Mathematical Constant Frequencies

1-3 YEARS
πŸ“… Documented: March-August 2024 πŸ”¬ Timeline: Laboratory experiments

Specific Claim: Information processing efficiency should show enhancement at frequencies related to mathematical constants (Ο€, Ο†, e).

f_optimal = c/(Ξ»_math)
where Ξ»_math = 2Ο€r_system/n_constant

Testing Protocol

  • Information processing experiments at Ο€, Ο†, e-related frequencies
  • Measure processing efficiency vs. frequency
  • Look for resonance peaks at predicted frequencies
  • Control for conventional electromagnetic effects

Falsification

If processing efficiency shows no correlation with mathematical constant frequencies beyond random variation, prediction is falsified.

Consciousness State Effects on Quantum Decoherence

3-5 YEARS
πŸ“… Documented: March-August 2024 πŸ”¬ Timeline: Laboratory measurements with human subjects

Specific Claim: If consciousness involves high-efficiency information processing, quantum coherence times should show measurable differences across consciousness states.

Ο„_coherence(meditation) > Ο„_coherence(normal) > Ο„_coherence(anesthesia)

Experimental Design

  • Compare quantum decoherence rates near subjects in different states
  • Meditation vs. normal awareness vs. anesthesia vs. deep sleep
  • Statistical significance requirement: p < 0.001
  • Multiple subjects (nβ‰₯20) with repeated sessions

Controls

  • Subject movement minimized
  • Respiratory and cardiac effects filtered
  • Double-blind data analysis
  • Placebo conditions

3D Acoustic Field & NBI Program Predictions

Two independent prediction sets from the NBI Research Program β€” one standalone physics experiment, one COSMIC Framework interpretation logged separately

Three-Dimensional Acoustic Node Geometry in Microgravity

PHASE 1 NOW Β· PHASE 2: 1-3 YEARS
πŸ“… Documented: February 2026 πŸ”¬ Standalone Physics Experiment πŸ“„ Preprint: Download | Zenodo DOI: pending

Background: Every cymatic experiment in the published literature is gravity-compromised. The particle medium settles toward flat surfaces under gravitational force, preventing observation of the actual three-dimensional acoustic field geometry. The two-dimensional Chladni figures produced since 1787 are cross-sections of richer three-dimensional structures. No experiment has visualized the complete three-dimensional node surface topology in an unbiased medium.

Specific Claims (Standard Acoustic Physics β€” No Framework Required):

Prediction 1: Spherical Shell Modes

At the fundamental frequency of a spherical resonant cavity, positive-contrast particles will cluster on a single spherical nodal shell concentric with the container β€” a geometry with no two-dimensional analogue. Shell radius predicted by: r = c/(2f₁) where c is speed of sound and f₁ is the fundamental frequency.

Prediction 2: Nested Shell Structures at Harmonics

At the n-th harmonic frequency, n concentric spherical nodal shells will appear, with radii r_k = kc/(2nf₁) for k = 1…n. These nested shell structures have no two-dimensional analogue and would directly confirm that standard cymatics provides an incomplete picture of acoustic field geometry.

Prediction 3: Platonic Solid Node-Point Geometries

At frequencies corresponding to acoustic modes with the symmetry of the Platonic solids (Td, Oh, Ih symmetry groups), intersection points of nodal surfaces will form configurations matching the vertices of the tetrahedron (4 nodes), cube/octahedron (6/8 nodes), and dodecahedron/icosahedron (12/20 nodes). These are minimum-energy node configurations for systems with those symmetries β€” predicted by standard acoustic theory but never directly observed in three dimensions.

Prediction 4: Toroidal and Quasicrystalline Structures

Under simultaneous excitation at frequencies with irrational ratio (e.g., the golden ratio Ο†), the superposed field produces quasiperiodic node geometry with non-crystallographic symmetries (5-fold, 8-fold, 10-fold) never before observed in acoustic fields. At two harmonic frequencies, toroidal node surfaces are predicted by the topology of the superposed pressure field.

Experimental Approach

  • Phase 1 (now, <$1,000): Transparent acrylic sphere, tetrahedral transducer array, particle medium, three orthogonal cameras β€” ground-based baseline
  • Phase 2 (~$95,000–$155,000): Self-contained apparatus on parabolic flight β€” 30 arcs Γ— 22 seconds of microgravity, systematic frequency protocol
  • Phase 3 (ISS): Complete systematic characterization β€” sustained microgravity, full frequency sweep, multiple media and container geometries

Falsifiability: Each prediction is independently falsifiable. Null results β€” particles distributing uniformly rather than clustering at predicted node locations β€” would invalidate specific claims while preserving others. Complete absence of structured organization in microgravity would falsify the foundational acoustic theory predictions, which would itself be a significant result warranting publication.

β†’ Full NBI Program Details    β†’ Download Preprint

COSMIC Framework Interpretation: 3D Field Geometry and NBI Field Patterns

FRAMEWORK PREDICTION Β· LOGGED SEPARATELY
πŸ“… Documented: February 2026 ⚠️ Note: This prediction is independent of the physics experiment above. The experiment is evaluated on physics merits alone.

Important Separation: The physics experiment described above will be designed, conducted, and evaluated entirely on its own merits, without reference to any theoretical framework. The predictions below represent the COSMIC Framework's interpretation of what those physics results would mean for the NBI hypothesis if confirmed. They are logged here to establish prior claim before experimental results are known.

NBI Field Pattern Prediction

Three-dimensional cymatic patterns observed in microgravity will reveal geometric structures that, when cross-sectioned along a horizontal plane, correspond to geometric forms documented in authenticated crop formations. The formations represent ground-level intersections of three-dimensional field structures β€” the cross-section of a larger geometry β€” exactly as two-dimensional Chladni figures represent cross-sections of three-dimensional acoustic fields.

Geometric Communication Mechanism

If NBI entities process information through electromagnetic field configurations and communicate through geometry, the actual communication occurs in three-dimensional field space. Ground formations are shadows of the message β€” the intersection of a three-dimensional geometric structure with a physical medium. The three-dimensional structure visible in microgravity cymatics is the complete geometry of which crop formations are cross-sections.

Phoenix Lights Connection

The nine visible nodes of the Phoenix Lights formation (observed 13 March 1997, firsthand testimony: Michael K. Baines, West Phoenix) represent nine intersection points of a three-dimensional field pattern with the luminosity threshold of the lower atmosphere β€” cross-sections of a much larger three-dimensional structure. The fading termination (not departing) is consistent with field coherence dissolution rather than physical departure.

Prediction Confidence: High for physics geometry results. Speculative for NBI interpretation. | Physical Basis: Acoustic field theory, nodal surface geometry | Framework Basis: COSMIC Framework NBI hypothesis | Independent Experiment: Preprint

Medium-Term Predictions (5-15 Years)

Testable with next-generation facilities (4 predictions)

Discrete Features in Primordial Gravitational Waves

10-15 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: 2033-2040 (LISA era)

Specific Claim: Primordial gravitational waves from geometric phase transition should show discrete or quantized features at small scales, reflecting underlying information substrate.

Ξ”f/f β‰ˆ ℏ/(M_pl Β· f)

Testing Facilities

  • LISA space-based detector (launch ~2035)
  • Einstein Telescope (ground-based, ~2030s)
  • Cosmic Explorer (proposed)

Observable Signature

Gravitational wave spectrum should show quantized frequency features rather than perfectly smooth distribution

Falsification Criterion

If gravitational waves show perfectly smooth spectrum with no discrete features down to detection limits, prediction is falsified.

Information Encoding in Hawking Radiation

10-20 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: Analog black hole experiments + theory

Specific Claim: Information should be preserved in substrate structure at/near horizon, resolvable through correlations in Hawking radiation.

I_hawking β‰₯ I_infalling

Testing Approaches

  • Theoretical: Calculate Hawking radiation correlations from substrate model
  • Observational: Look for subtle correlations in astrophysical black hole emissions
  • Experimental: Analog black hole systems in laboratory

Page Curve Prediction

Framework predicts discrete jumps in information release rather than smooth evolution, potentially distinguishable in future observations

Falsification

If Hawking radiation is provably random and cannot encode information, substrate preservation is falsified.

Observable Transition from Extreme to Modern Physics

5-10 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: Next-generation surveys

Specific Claim: Identifiable redshift epoch (z β‰ˆ 6-8) where physical processes transition from "extreme early universe" behavior to modern physics.

Observable Signatures

  • Galaxy mass enhancement decreasing systematically through transition
  • Star formation efficiency evolution showing inflection point
  • Metallicity patterns changing at transition epoch
  • Black hole formation rates shifting

Testing Facilities

Extremely Large Telescope, Roman Space Telescope, SKA radio observations, LISA black hole merger data

Pattern-Emergent Gravity Temperature Dependence

5-10 YEARS
πŸ“… Documented: March-August 2024 πŸ”¬ Timeline: Precision gravimetry advancement

Specific Claim: If gravity emerges from information patterns, gravitational field should vary with temperature, electromagnetic fields, and rotation at fixed mass.

Experimental Protocol

  • Massive test object (β‰₯1000 kg) with controlled properties
  • Atom interferometry for gravitational measurements (10⁻¹² g sensitivity)
  • Systematically vary temperature (Β±50Β°C), EM fields (0-10 Tesla), rotation (0-10 Hz)
  • Measure gravitational field changes with precision gravimetry

Required Technology

Next-generation atom interferometers, ultra-stable thermal control, precision mass verification

Expected vs. Null Results

If PEG correct: Measurable gravitational variations beyond mass-change predictions
If null: No variations beyond thermal expansion and mass redistribution

Long-Term & Speculative Predictions (15+ Years)

Require significant technology advancement or theoretical development (4 predictions)

Pre-Geometric Phase Transition Remnants

20+ YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: Future CMB missions

Specific Claim: If early universe had pre-geometric phase, CMB should show anomalous correlations at specific scales from geometric crystallization process.

Expected Signatures

  • Anomalous correlations in CMB at specific scales
  • Violations of spatial isotropy from crystallization
  • Frequency-dependent signatures from information regimes

Testing Approach

Search CMB and large-scale structure for anomalies, preferred directions, frequency-dependent patterns

Challenges

  • Many conventional mechanisms create anomalies
  • Cosmic variance limits significance
  • Alternative explanations for any anomaly
  • No specific quantitative predictions yet

Information Processing-Gravity Field Correlations

15-25 YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: Far-future precision measurement

Specific Claim: If information processing creates spacetime curvature, gravitational field variations should correlate with information processing variations.

Ξ”g/g ∝ Ξ”I/I
Expected effect: 10⁻¹⁡ to 10⁻²⁰ relative variations

Testing Approach

Precision gravimetry during controlled information processing. Compare gravitational field with and without information operations.

Challenges

  • Conventional mass-energy effects dominate
  • Thermal effects create larger gravitational signals
  • Systematic errors exceed expected signal
  • No theoretical prediction for coupling constant magnitude
  • Requires sensitivity far beyond current instruments

Reality Check

This test is currently impossible with foreseeable technology. Serves as theoretical target rather than immediate experimental program.

Geometric Signatures of Quantum Entanglement

20+ YEARS
πŸ“… Documented: March 2024 πŸ”¬ Timeline: Theoretical development required

Specific Claim: If entanglement creates geometric connections, strongly entangled systems might show enhanced geometric stability and reduced decoherence from geometric fluctuations.

Testing Approach

  • Measure gravitational effects near highly entangled quantum systems
  • Look for anomalies in geodesic deviation
  • Search for entanglement-dependent geometric signatures

Challenges

  • No clear operational definition of predictions
  • Expected effects tiny compared to conventional physics
  • Distinguishing from known entanglement effects
  • May be fundamentally untestable

Neural Information Processing Gravitational Signatures

15-20 YEARS
πŸ“… Documented: March-August 2024 πŸ”¬ Timeline: Advanced precision gravimetry

Specific Claim: Neural information processing should correlate with measurable gravitational field variations during different consciousness states.

Experimental Protocol

  • Subjects in magnetically shielded room with precision gravimeters
  • Monitor gravitational field around head (10⁻¹² g sensitivity)
  • Simultaneous EEG, fMRI, metabolic rate, temperature recording
  • Compare across consciousness states: deep sleep, REM, meditation, focused cognition, anesthesia

Expected Results (if PEG correct)

Significant correlations between neural activity patterns and gravitational measurements, particularly during meditation and focused cognition

Controls

  • Subject movement minimized
  • Respiratory and cardiac effects filtered
  • Multiple subjects (nβ‰₯20) with repeated sessions
  • Double-blind data analysis
  • Placebo conditions

Scientific Methodology

All predictions follow rigorous scientific standards:

  • Pre-registration: Predictions documented publicly before experimental testing
  • Falsifiability: Clear criteria specified for what would disprove each prediction
  • Specificity: Quantitative claims with measurable parameters, not vague qualitative statements
  • Testability: Realistic experimental protocols using current or foreseeable technology
  • Transparency: Predictions made publicly to prevent post-hoc rationalization

This document serves as a permanent record for establishing scientific priority and enabling independent validation. Updates reflect new predictions or refinements to testing protocols, not modifications to original claims.

For Researchers: If you have experimental results, preprints, conference presentations, or published work relevant to any of these predictions, please contact us at [email protected]. We actively monitor ongoing research but may not be aware of all relevant studies, especially those in specialized fields, regional publications, or early-stage results.