Results

HGT — Hallucination Detection

Model	Dataset	Method	AUROC	F1	Precision	Recall
GPT-2	Wiki Bio	SAPLMA	0.71	0.68	0.72	0.65
GPT-2	Wiki Bio	SelfCheckGPT	0.74	0.70	0.75	0.66
GPT-2	Wiki Bio	PHANTASM HGT	0.79	0.76	0.80	0.72
LLaMA-7B	Vectara HFB	Fact-checker	0.76	0.73	0.78	0.69
LLaMA-7B	Vectara HFB	PHANTASM HGT	0.83	0.80	0.85	0.76

UC — Calibration

Model	Method	ECE ↓	MCE ↓
GPT-2	Baseline	0.187	0.312
GPT-2	Temperature scaling	0.089	0.201
GPT-2	PHANTASM UC	0.041	0.098
LLaMA-7B	Baseline	0.143	0.267
LLaMA-7B	PHANTASM UC	0.029	0.071

CMN — Hypothesis Quality

Domain	Method	Novelty@5	Expert Acceptance Rate
Drug discovery	Filtered LLM	0.08	7%
Drug discovery	PHANTASM CMN	0.67	54%
Material science	Filtered LLM	0.11	9%
Material science	PHANTASM CMN	0.61	48%

PHANTASM Score

The composite PHANTASM score combines all three pillars:

PHANTASM_score = 0.4 * HGT_F1  +  0.3 * CMN_Novelty@5  +  0.3 * (1 - UC_ECE)

Model	PHANTASM Score
GPT-2 (baseline)	0.421
GPT-2 + PHANTASM	0.701
LLaMA-7B + PHANTASM	0.774