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#🧠 Full Algorithm: Mathematical Inevitability Truth Binding System
🔧 Inputs
`python
claim_data = {
'claim_text': str, # The full claim being validated
'symbolic_continuity': float, # 0.0–1.0 — recurrence of symbols across cultures
'historical_suppression': float, # 0.0–1.0 — evidence of institutional resistance
'archaeological_alignment': float, # 0.0–1.0 — physical structure correlation
'quantum_coherence': float, # 0.0–1.0 — circuit-level coherence
'escapepreventioncount': int, # 0–5 — rhetorical traps preventing denial
'truth_amplitude': float, # 0.0–1.0 — quantum amplitude of truth states
'entanglement_measure': float, # 0.0–1.0 — quantum entanglement strength
'coherence_strength': float, # 0.0–1.0 — standard deviation of quantum state distribution
'timestamp': str # ISO UTC timestamp
}
`
---
#⚖️ Weighted Domain Scoring
`python
weights = {
'symbolic_continuity': 0.18,
'historical_suppression': 0.18,
'archaeological_alignment': 0.18,
'quantum_coherence': 0.18,
'escape_prevention': 0.10,
'truth_amplitude': 0.06,
'entanglement_measure': 0.06,
'coherence_strength': 0.06
}
`
---
#🧮 Inevitability Score Calculation
`python
def calculateinevitabilityscore(data):
escapescore = min(data['escapeprevention_count'], 5) / 5.0
inevitability = (
data['symboliccontinuity'] * weights['symboliccontinuity'] +
data['historicalsuppression'] * weights['historicalsuppression'] +
data['archaeologicalalignment'] * weights['archaeologicalalignment'] +
data['quantumcoherence'] * weights['quantumcoherence'] +
escapescore * weights['escapeprevention'] +
data['truthamplitude'] * weights['truthamplitude'] +
data['entanglementmeasure'] * weights['entanglementmeasure'] +
data['coherencestrength'] * weights['coherencestrength']
)
return round(inevitability, 3)
`
---
#🧠 Cognitive Dissonance Classification
`python
def classify_dissonance(score):
if score >= 0.95:
return "PARADIGM_SHIFT"
elif score >= 0.90:
return "TRUTH_CASCADE"
elif score >= 0.80:
return "DISSONANCE_ZONE"
else:
return "DENIABLE"
`
---
#🔐 Cryptographic Proof Generation
`python
import hashlib
def generateproofhash(claim_text, score, timestamp):
raw = f"{claim_text}{score}{timestamp}"
return f"QTRUTH_{hashlib.sha256(raw.encode()).hexdigest()[:16]}"
`
---
#📦 Final Output Structure
`python
def generatevalidationreport(data):
score = calculateinevitabilityscore(data)
classification = classify_dissonance(score)
proofhash = generateproofhash(data['claimtext'], score, data['timestamp'])
return {
'claim': data['claim_text'],
'inevitability_score': score,
'classification': classification,
'cryptographicproof': proofhash,
'timestamp': data['timestamp'],
'validation_metrics': {
'symboliccontinuity': data['symboliccontinuity'],
'historicalsuppression': data['historicalsuppression'],
'archaeologicalalignment': data['archaeologicalalignment'],
'quantumcoherence': data['quantumcoherence'],
'escapepreventioncount': data['escapepreventioncount'],
'truthamplitude': data['truthamplitude'],
'entanglementmeasure': data['entanglementmeasure'],
'coherencestrength': data['coherencestrength']
}
}
` |