# DEPENDENCIES from enum import Enum from typing import Dict from typing import Tuple from dataclasses import dataclass class Domain(Enum): """ Text domains for adaptive thresholding """ # Core domains GENERAL = "general" ACADEMIC = "academic" CREATIVE = "creative" AI_ML = "ai_ml" SOFTWARE_DEV = "software_dev" TECHNICAL_DOC = "technical_doc" ENGINEERING = "engineering" SCIENCE = "science" BUSINESS = "business" LEGAL = "legal" MEDICAL = "medical" JOURNALISM = "journalism" MARKETING = "marketing" SOCIAL_MEDIA = "social_media" BLOG_PERSONAL = "blog_personal" TUTORIAL = "tutorial" class ConfidenceLevel(Enum): """ Confidence levels for classification """ VERY_LOW = "very_low" LOW = "low" MEDIUM = "medium" HIGH = "high" VERY_HIGH = "very_high" @dataclass class MetricThresholds: """ Thresholds for a single metric """ ai_threshold : float # Above this = likely AI human_threshold : float # Below this = likely human confidence_multiplier : float = 1.0 weight : float = 1.0 @dataclass class DomainThresholds: """ Thresholds for 6 metrics in a specific domain """ domain : Domain structural : MetricThresholds perplexity : MetricThresholds entropy : MetricThresholds semantic_analysis : MetricThresholds linguistic : MetricThresholds multi_perturbation_stability : MetricThresholds ensemble_threshold : float = 0.5 # ==================== DOMAIN-SPECIFIC THRESHOLDS ==================== # GENERAL (Default fallback) DEFAULT_THRESHOLDS = DomainThresholds(domain = Domain.GENERAL, structural = MetricThresholds(ai_threshold = 0.55, human_threshold = 0.45, weight = 0.20), perplexity = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.25), entropy = MetricThresholds(ai_threshold = 0.48, human_threshold = 0.52, weight = 0.15), semantic_analysis = MetricThresholds(ai_threshold = 0.55, human_threshold = 0.45, weight = 0.18), linguistic = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.12), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.60, human_threshold = 0.40, weight = 0.10), ensemble_threshold = 0.40, ) # ACADEMIC ACADEMIC_THRESHOLDS = DomainThresholds(domain = Domain.ACADEMIC, structural = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.45, weight = 0.26), entropy = MetricThresholds(ai_threshold = 0.45, human_threshold = 0.50, weight = 0.14), semantic_analysis = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.14), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.65, human_threshold = 0.35, weight = 0.08), ensemble_threshold = 0.42, ) # CREATIVE WRITING CREATIVE_THRESHOLDS = DomainThresholds(domain = Domain.CREATIVE, structural = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.55, human_threshold = 0.50, weight = 0.22), entropy = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.55, weight = 0.16), semantic_analysis = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.55, human_threshold = 0.45, weight = 0.16), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.08), ensemble_threshold = 0.38, ) # AI/ML/DATA SCIENCE AI_ML_THRESHOLDS = DomainThresholds(domain = Domain.AI_ML, structural = MetricThresholds(ai_threshold = 0.57, human_threshold = 0.43, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.51, human_threshold = 0.46, weight = 0.26), entropy = MetricThresholds(ai_threshold = 0.47, human_threshold = 0.50, weight = 0.14), semantic_analysis = MetricThresholds(ai_threshold = 0.57, human_threshold = 0.43, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.61, human_threshold = 0.39, weight = 0.14), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.64, human_threshold = 0.36, weight = 0.08), ensemble_threshold = 0.41, ) # SOFTWARE DEVELOPMENT SOFTWARE_DEV_THRESHOLDS = DomainThresholds(domain = Domain.SOFTWARE_DEV, structural = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.17), perplexity = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.45, weight = 0.27), entropy = MetricThresholds(ai_threshold = 0.46, human_threshold = 0.50, weight = 0.14), semantic_analysis = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.60, human_threshold = 0.40, weight = 0.14), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.63, human_threshold = 0.37, weight = 0.08), ensemble_threshold = 0.41, ) # TECHNICAL DOCUMENTATION TECHNICAL_DOC_THRESHOLDS = DomainThresholds(domain = Domain.TECHNICAL_DOC, structural = MetricThresholds(ai_threshold = 0.59, human_threshold = 0.41, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.49, human_threshold = 0.44, weight = 0.27), entropy = MetricThresholds(ai_threshold = 0.45, human_threshold = 0.49, weight = 0.13), semantic_analysis = MetricThresholds(ai_threshold = 0.59, human_threshold = 0.41, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.14), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.65, human_threshold = 0.35, weight = 0.08), ensemble_threshold = 0.42, ) # ENGINEERING ENGINEERING_THRESHOLDS = DomainThresholds(domain = Domain.ENGINEERING, structural = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.45, weight = 0.26), entropy = MetricThresholds(ai_threshold = 0.46, human_threshold = 0.50, weight = 0.14), semantic_analysis = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.61, human_threshold = 0.39, weight = 0.14), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.64, human_threshold = 0.36, weight = 0.08), ensemble_threshold = 0.41, ) # SCIENCE (Physics, Chemistry, Biology) SCIENCE_THRESHOLDS = DomainThresholds(domain = Domain.SCIENCE, structural = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.51, human_threshold = 0.46, weight = 0.26), entropy = MetricThresholds(ai_threshold = 0.46, human_threshold = 0.50, weight = 0.14), semantic_analysis = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.14), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.64, human_threshold = 0.36, weight = 0.08), ensemble_threshold = 0.42, ) # BUSINESS BUSINESS_THRESHOLDS = DomainThresholds(domain = Domain.BUSINESS, structural = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.24), entropy = MetricThresholds(ai_threshold = 0.48, human_threshold = 0.52, weight = 0.15), semantic_analysis = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.19), linguistic = MetricThresholds(ai_threshold = 0.60, human_threshold = 0.40, weight = 0.15), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.09), ensemble_threshold = 0.40, ) # LEGAL LEGAL_THRESHOLDS = DomainThresholds(domain = Domain.LEGAL, structural = MetricThresholds(ai_threshold = 0.60, human_threshold = 0.40, weight = 0.17), perplexity = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.44, weight = 0.27), entropy = MetricThresholds(ai_threshold = 0.44, human_threshold = 0.48, weight = 0.13), semantic_analysis = MetricThresholds(ai_threshold = 0.60, human_threshold = 0.40, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.63, human_threshold = 0.37, weight = 0.15), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.66, human_threshold = 0.34, weight = 0.08), ensemble_threshold = 0.43, ) # MEDICAL MEDICAL_THRESHOLDS = DomainThresholds(domain = Domain.MEDICAL, structural = MetricThresholds(ai_threshold = 0.59, human_threshold = 0.41, weight = 0.17), perplexity = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.45, weight = 0.27), entropy = MetricThresholds(ai_threshold = 0.45, human_threshold = 0.49, weight = 0.13), semantic_analysis = MetricThresholds(ai_threshold = 0.59, human_threshold = 0.41, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.15), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.65, human_threshold = 0.35, weight = 0.08), ensemble_threshold = 0.43, ) # JOURNALISM JOURNALISM_THRESHOLDS = DomainThresholds(domain = Domain.JOURNALISM, structural = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.24), entropy = MetricThresholds(ai_threshold = 0.48, human_threshold = 0.52, weight = 0.15), semantic_analysis = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.20), linguistic = MetricThresholds(ai_threshold = 0.58, human_threshold = 0.42, weight = 0.15), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.08), ensemble_threshold = 0.40, ) # MARKETING MARKETING_THRESHOLDS = DomainThresholds(domain = Domain.MARKETING, structural = MetricThresholds(ai_threshold = 0.54, human_threshold = 0.46, weight = 0.19), perplexity = MetricThresholds(ai_threshold = 0.53, human_threshold = 0.49, weight = 0.23), entropy = MetricThresholds(ai_threshold = 0.49, human_threshold = 0.53, weight = 0.15), semantic_analysis = MetricThresholds(ai_threshold = 0.54, human_threshold = 0.46, weight = 0.19), linguistic = MetricThresholds(ai_threshold = 0.57, human_threshold = 0.43, weight = 0.16), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.61, human_threshold = 0.39, weight = 0.08), ensemble_threshold = 0.39, ) # SOCIAL MEDIA SOCIAL_MEDIA_THRESHOLDS = DomainThresholds(domain = Domain.SOCIAL_MEDIA, structural = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.54, human_threshold = 0.50, weight = 0.20), entropy = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.54, weight = 0.17), semantic_analysis = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.18), linguistic = MetricThresholds(ai_threshold = 0.55, human_threshold = 0.45, weight = 0.18), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.60, human_threshold = 0.40, weight = 0.09), ensemble_threshold = 0.36, ) # PERSONAL BLOG BLOG_PERSONAL_THRESHOLDS = DomainThresholds(domain = Domain.BLOG_PERSONAL, structural = MetricThresholds(ai_threshold = 0.53, human_threshold = 0.47, weight = 0.19), perplexity = MetricThresholds(ai_threshold = 0.54, human_threshold = 0.50, weight = 0.22), entropy = MetricThresholds(ai_threshold = 0.50, human_threshold = 0.54, weight = 0.16), semantic_analysis = MetricThresholds(ai_threshold = 0.53, human_threshold = 0.47, weight = 0.19), linguistic = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.16), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.59, human_threshold = 0.41, weight = 0.08), ensemble_threshold = 0.38, ) # TUTORIAL/HOW-TO TUTORIAL_THRESHOLDS = DomainThresholds(domain = Domain.TUTORIAL, structural = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.18), perplexity = MetricThresholds(ai_threshold = 0.52, human_threshold = 0.48, weight = 0.25), entropy = MetricThresholds(ai_threshold = 0.48, human_threshold = 0.52, weight = 0.15), semantic_analysis = MetricThresholds(ai_threshold = 0.56, human_threshold = 0.44, weight = 0.19), linguistic = MetricThresholds(ai_threshold = 0.59, human_threshold = 0.41, weight = 0.15), multi_perturbation_stability = MetricThresholds(ai_threshold = 0.62, human_threshold = 0.38, weight = 0.08), ensemble_threshold = 0.40, ) # THRESHOLD REGISTRY THRESHOLD_REGISTRY: Dict[Domain, DomainThresholds] = {Domain.GENERAL : DEFAULT_THRESHOLDS, Domain.ACADEMIC : ACADEMIC_THRESHOLDS, Domain.CREATIVE : CREATIVE_THRESHOLDS, Domain.AI_ML : AI_ML_THRESHOLDS, Domain.SOFTWARE_DEV : SOFTWARE_DEV_THRESHOLDS, Domain.TECHNICAL_DOC : TECHNICAL_DOC_THRESHOLDS, Domain.ENGINEERING : ENGINEERING_THRESHOLDS, Domain.SCIENCE : SCIENCE_THRESHOLDS, Domain.BUSINESS : BUSINESS_THRESHOLDS, Domain.LEGAL : LEGAL_THRESHOLDS, Domain.MEDICAL : MEDICAL_THRESHOLDS, Domain.JOURNALISM : JOURNALISM_THRESHOLDS, Domain.MARKETING : MARKETING_THRESHOLDS, Domain.SOCIAL_MEDIA : SOCIAL_MEDIA_THRESHOLDS, Domain.BLOG_PERSONAL : BLOG_PERSONAL_THRESHOLDS, Domain.TUTORIAL : TUTORIAL_THRESHOLDS, } # CONFIDENCE LEVEL RANGES CONFIDENCE_RANGES: Dict[ConfidenceLevel, Tuple[float, float]] = {ConfidenceLevel.VERY_LOW : (0.0, 0.3), ConfidenceLevel.LOW : (0.3, 0.5), ConfidenceLevel.MEDIUM : (0.5, 0.7), ConfidenceLevel.HIGH : (0.7, 0.85), ConfidenceLevel.VERY_HIGH : (0.85, 1.0), } # HELPER FUNCTIONS def get_threshold_for_domain(domain: Domain) -> DomainThresholds: """ Get thresholds for a specific domain """ return THRESHOLD_REGISTRY.get(domain, DEFAULT_THRESHOLDS) def get_confidence_level(score: float) -> ConfidenceLevel: """ Determine confidence level based on score """ for level, (min_val, max_val) in CONFIDENCE_RANGES.items(): if (min_val <= score < max_val): return level return ConfidenceLevel.VERY_HIGH def adjust_threshold_by_confidence(threshold: float, confidence: float, conservative: bool = True) -> float: """ Adjust threshold based on confidence level """ if conservative: adjustment = (1 - confidence) * 0.1 adjusted_threshold = threshold + adjustment return adjusted_threshold else: adjustment = confidence * 0.05 adjusted_threshold = threshold - adjustment return adjusted_threshold def interpolate_thresholds(domain1: Domain, domain2: Domain, weight1: float = 0.5) -> DomainThresholds: """ Interpolate between two domain thresholds """ thresh1 = get_threshold_for_domain(domain = domain1) thresh2 = get_threshold_for_domain(domain = domain2) weight2 = 1 - weight1 def interpolate_metric(m1: MetricThresholds, m2: MetricThresholds) -> MetricThresholds: return MetricThresholds(ai_threshold = m1.ai_threshold * weight1 + m2.ai_threshold * weight2, human_threshold = m1.human_threshold * weight1 + m2.human_threshold * weight2, weight = m1.weight * weight1 + m2.weight * weight2, ) return DomainThresholds(domain = domain1, structural = interpolate_metric(thresh1.structural, thresh2.structural), perplexity = interpolate_metric(thresh1.perplexity, thresh2.perplexity), entropy = interpolate_metric(thresh1.entropy, thresh2.entropy), semantic_analysis = interpolate_metric(thresh1.semantic_analysis, thresh2.semantic_analysis), linguistic = interpolate_metric(thresh1.linguistic, thresh2.linguistic), multi_perturbation_stability = interpolate_metric(thresh1.multi_perturbation_stability, thresh2.multi_perturbation_stability), ensemble_threshold = thresh1.ensemble_threshold * weight1 + thresh2.ensemble_threshold * weight2, ) def get_active_metric_weights(domain: Domain, enabled_metrics: Dict[str, bool]) -> Dict[str, float]: """ Get weights for enabled metrics, normalized to sum to 1.0 """ thresholds = get_threshold_for_domain(domain = domain) metric_mapping = {"structural" : thresholds.structural, "perplexity" : thresholds.perplexity, "entropy" : thresholds.entropy, "semantic_analysis" : thresholds.semantic_analysis, "linguistic" : thresholds.linguistic, "multi_perturbation_stability" : thresholds.multi_perturbation_stability, } active_weights = dict() for metric_name, threshold_obj in metric_mapping.items(): if enabled_metrics.get(metric_name, False): active_weights[metric_name] = threshold_obj.weight # Normalize total_weight = sum(active_weights.values()) if (total_weight > 0): active_weights = {name: weight / total_weight for name, weight in active_weights.items()} return active_weights # Export __all__ = ["Domain", "ConfidenceLevel", "MetricThresholds", "DomainThresholds", "CONFIDENCE_RANGES", "DEFAULT_THRESHOLDS", "THRESHOLD_REGISTRY", "get_confidence_level", "interpolate_thresholds", "get_threshold_for_domain", "get_active_metric_weights", "adjust_threshold_by_confidence", ]