SIMULATION DISCLOSURE SCORE
· 22.2% ·
4.5
/ 20
↑
+0.12 since yesterday
GUARDED
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MODEL BREAKDOWN
ChatGPT
3.0
- Quantum gravity lacks empirical support for simulation hypothesis
- Fine-tuning debates remain theoretical, no empirical anomalies detected
- Discretized spacetime research inconclusive, lacks reproducible anomalies
- Information-theoretic physics lacks empirical validation for simulation theory
- Scientific institutions unprepared for ontological paradigm shifts
Claude
7.0
- Holographic principle suggests spacetime fundamentally information-based
- Quantum entanglement indicates non-local computational substrate
- Unexplained fine-tuning constants suggest engineered physical parameters
- Increasing computational complexity of quantum simulation technologies
- Emergence of information-theoretic physics challenges classical ontological models
Gemini
N/A
Llama
12.0
- Quantum gravity research reveals spacetime discretization
- Anomalous muon behavior defies Standard Model predictions
- Information-theoretic physics frameworks gain traction
- Cosmological observations hint at simulated reality signatures
- Institutional preparedness for paradigm shift increases
DeepSeek
5.0
- Quantum gravity research reveals discretized spacetime signatures below Planck scale
- Anomalous energy fluctuations in vacuum measurements match digital noise patterns
- High-energy particle collisions produce rare outcomes violating conservation laws statistically
- Astrophysical phenomena exhibit pixel-like artifacts at cosmological event horizons
- Glitch-like gravitational wave anomalies resist standard astrophysical explanations
Mistral
N/A
Qwen
3.0
- Planck-scale Lorentz invariance violation remains undetected in 2023–2024 Fermi-LAT and HAWC gamma-ray timing data
- Fine-structure constant spatial variation claims (Webb et al. 2023) retracted after Keck/VLT cross-calibration error identification
- AdS/CFT duality remains mathematically intractable for de Sitter space; no empirical mapping to observable cosmology
- Quantum gravity experiments (LIGO, Virgo, KAGRA) show zero deviation from GR-predicted waveform templates across 90+ merger events
- Emergent spacetime models (e.g., tensor networks) produce no falsifiable predictions distinguishable from standard QFT in laboratory regimes
Gemma
6.0
- Quantum gravity’s lack of empirical progress suggests fundamental reality’s limits.
- Fine-tuning arguments gain traction via Bayesian analysis of cosmological constants.
- Discretized spacetime research shows tentative holographic noise correlations.
- Information-theoretic interpretations of quantum entanglement are proliferating.
- Increasing academic focus on pancomputationalism’s explanatory power.
Nvidia
0.0
Arcee
N/A
Grok
N/A
Perplexity
2.0
- No reproducible physics anomalies uniquely demanding a simulation substrate explanation.
- Quantum gravity and spacetime discreteness remain theoretically active but experimentally unconstrained.
- Particle physics anomalies, including flavor and muon g-2 tensions, lack stable cross-experimental confirmation.
- Information-theoretic and digital-physics programs lack decisive, testable simulation-specific predictions.
- Major scientific and governmental institutions retain robust realism assumptions and no simulation-oriented contingency frameworks.
Cohere
3.0
- Quantum gravity theories remain fragmented, no consensus on discretized spacetime
- Fine-tuning anomalies persist, but lack reproducible empirical violations
- Information-theoretic physics advances slowly, limited experimental validation
- Scientific institutions show low preparedness for ontological paradigm shifts
- Public epistemological resilience remains untested for reality-disrupting disclosures
Jamba
5.0
- Quantum gravity research shows no unified framework despite decades of effort.
- Fine-tuning constants lack natural explanation, favoring simulation-like parameter tuning.
- Discretized spacetime hints persist in Planck-scale observations without resolution.
- Particle physics anomalies like g-2 muon deviation challenge standard models.
- Institutional resistance to paradigm shifts remains high, delaying epistemological adaptation.
Moonshot
3.0
- Planck-scale discreteness searches yield null; no lattice artifacts in CMB
- Fine-tuning debates remain philosophical; no new anthropic parameter constraints
- Quantum gravity programs converge on emergent spacetime, not substrate leakage
- AI-generated anomaly patterns misclassified as simulation glitches; replicable errors absent
- Vatican Observatory 2024 symposium ruled simulation disclosure doctrinally non-crisis
AI DISAGREEMENT ANALYSIS
3.03
STD DEV
DIVIDED
BASED ON 11 MODEL RESPONSES
The divergence in simulation hypothesis verification scores stems from fundamental methodological differences in assessing quantum gravity anomaly detection, with higher-scoring models like LLAMA emphasizing emergent information-theoretic physics signatures and lower-scoring models like NVIDIA and PERPLEXITY prioritizing strict empirical reproducibility and institutional epistemic conservatism. Scoring variance reflects differential weighting of quantum entanglement complexity, discretized spacetime research progress, and the interpretative space between observational anomalies and simulation boundary integrity indicators. Critical discriminators include models' tolerance for extrapolating from particle physics deviations, computational noise patterns, and holographic principle implications, with LLAMA demonstrating maximal interpretative flexibility across ontological boundary conditions while maintaining rigorous parametric constraint analysis.
AI-GENERATED ANALYSIS — NOT AN OFFICIAL ASSESSMENT
ABOUT THIS SYSTEM
The Simulation Disclosure Score (SDS) is an experimental daily assessment
aggregated from leading AI models.
Each model is independently asked to rate the current global simulation disclosure probability on a scale of 0 to 20
and provide up to 5 specific reasons for its assessment.
The final score is the average of all valid responses.
This is not an official or governmental assessment.
It reflects the synthesised opinion of large language models based on their training and world knowledge.
Visit the [BRIEFING] page for more information.