{"id":"W4231132425","doi":"10.1002/0470011815.b2a15081","title":"Loss Function","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Biostatistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Minimax; Frequentist inference; Decision theory; Bayesian probability; Function (biology); Computer science; Econometrics; Mathematics; Mathematical economics; Statistics; Bayesian inference","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":[0.008239939,0.00270551,0.002491178,0.002393959,0.0005967364,0.004759636,0.00331953,0.003488162,0.0154862],"category_scores_gemma":[0.02528696,0.0003662174,0.001364947,0.002593362,0.001685701,0.004008452,0.002565983,0.003530846,0.01044258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798675,"about_ca_system_score_gemma":0.001725414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009287033,"about_ca_topic_score_gemma":0.0003844397,"domain_scores_codex":[0.9913774,0.003245698,0.0006950664,0.001086309,0.003085767,0.0005098318],"domain_scores_gemma":[0.9905088,0.005607836,0.0006159379,0.001092245,0.001828008,0.0003472428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000800001,0.0004288746,0.002233277,0.0009780256,0.0003664261,0.0004722741,0.00007672516,0.2648647,0.002937175,0.1264136,0.09297024,0.5074587],"study_design_scores_gemma":[0.0001158358,0.0006197445,0.001242681,0.000610482,0.0002068019,0.001109072,0.00008329154,0.7225903,0.004607474,0.1897505,0.07896212,0.0001016663],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005270557,0.004898192,0.9712634,0.001950546,0.0009619734,0.0002553813,0.001160711,0.001473831,0.01276537],"genre_scores_gemma":[0.4394966,0.0136757,0.4378484,0.004575595,0.0035681,0.002572098,0.009390096,0.001725828,0.08714753],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0154862,"threshold_uncertainty_score":0.05180651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1799803768011715,"score_gpt":0.4710455843522139,"score_spread":0.2910652075510425,"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."}}