{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008345839,0.0004347108,0.001189764,0.0002313724,0.00002633533,0.00001228924,0.0003512859,0.000696335,0.02110708],"category_scores_gemma":[0.03883495,0.0003995513,0.0001673034,0.0002195695,0.0003600412,0.00001800295,0.0001097796,0.0004311236,0.0003822555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000397576,"about_ca_system_score_gemma":0.0001163841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003296314,"about_ca_topic_score_gemma":0.00004557416,"domain_scores_codex":[0.9969434,0.0003699307,0.001237376,0.0004851408,0.0006076562,0.0003564753],"domain_scores_gemma":[0.9811135,0.0167201,0.001132656,0.000757325,0.0001077599,0.0001686745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003304061,0.000143223,0.00003721655,0.0004433824,0.0001302767,0.00001616385,0.00001829969,1.123739e-7,0.000001450543,0.1707586,0.7585763,0.06984191],"study_design_scores_gemma":[0.0004100921,0.0001291163,0.00006006515,0.0002401377,0.0003498073,0.000002160882,0.000007881714,0.000008326449,0.000008685342,0.361566,0.6369115,0.0003061457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.000001389438,0.0002371907,0.2952416,0.0000485333,0.002194818,0.0004339772,0.002457346,0.0002020272,0.6991831],"genre_scores_gemma":[0.000006968088,0.001444697,0.5931199,0.00005407431,0.001680211,0.00001504842,0.00002509272,0.0004441239,0.4032098],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2978784,"threshold_uncertainty_score":0.9998456,"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."}}