{"id":"W6889596690","doi":"10.25934/pr00009377","title":"Biomarker discovery for immunotherapy response via pan-cancer and cancer-specific analyses","year":2025,"lang":"en","type":"dataset","venue":"Vivli","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Princess Margaret Cancer Centre","funders":"","keywords":"Biomarker discovery; Immunotherapy; Informatics; Immune checkpoint; Cancer; Clinical trial; Biomarker; Cancer immunotherapy; Cancer biomarkers","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02062238,0.001509385,0.003464602,0.007920421,0.0005843103,0.003301024,0.001104455,0.001125434,0.003096332],"category_scores_gemma":[0.03032215,0.0004883521,0.006205284,0.01088953,0.0006134365,0.001914448,0.001741008,0.001586368,0.0005441082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008562498,"about_ca_system_score_gemma":0.001447926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001736199,"about_ca_topic_score_gemma":0.002367579,"domain_scores_codex":[0.9910679,0.004557067,0.001025566,0.002238532,0.0007799724,0.0003308922],"domain_scores_gemma":[0.9817836,0.01066809,0.00346961,0.002239207,0.001455485,0.000384103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003492196,0.000287219,0.7106189,0.004918857,0.0538708,0.0005126145,0.0002964596,0.0208112,0.008319939,0.00446855,0.008999355,0.1834039],"study_design_scores_gemma":[0.0008330808,0.00309792,0.5406838,0.001612177,0.1028238,0.002411792,0.0008903921,0.1482108,0.01704478,0.09497688,0.08694673,0.000467972],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.4627023,0.1482816,0.3163181,0.009290704,0.001467761,0.001297259,0.0494343,0.002768431,0.008439616],"genre_scores_gemma":[0.9191117,0.006861488,0.05688406,0.001736658,0.0006414294,0.0006978565,0.01269895,0.0002538441,0.001113971],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02062238,"threshold_uncertainty_score":0.1090629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06698971287844391,"score_gpt":0.4013903195204984,"score_spread":0.3344006066420545,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}