{"id":"W4251890067","doi":"10.1002/9781118445112.stat05890","title":"Loss Function","year":2014,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","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); Expected utility hypothesis; Prospect theory; Computer science; Econometrics; Mathematics; Mathematical economics; Statistics; Bayesian inference; Artificial intelligence; Economics","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":["insufficient_payload"],"category_scores_codex":[0.001578348,0.001070291,0.002277946,0.0004150623,0.0001150453,0.0001062728,0.0008669875,0.001233814,0.02201766],"category_scores_gemma":[0.03994367,0.0009438619,0.0001782129,0.0003640123,0.0006377354,0.00004159934,0.0002913446,0.001516164,0.001564201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001455387,"about_ca_system_score_gemma":0.0002870785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001235598,"about_ca_topic_score_gemma":0.0005395635,"domain_scores_codex":[0.9931118,0.001250331,0.001992118,0.001365285,0.001312659,0.0009677469],"domain_scores_gemma":[0.9750677,0.02055467,0.001710869,0.001744315,0.0003858444,0.0005365706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009234667,0.0003282173,0.0000203531,0.0005922453,0.0002100838,0.00004030341,0.000008730405,5.370821e-7,0.000004738698,0.3423948,0.616125,0.04018263],"study_design_scores_gemma":[0.0008107355,0.0003469674,0.00003380349,0.0007234932,0.0004191258,0.000005291713,0.00001133458,0.0001659714,0.000002529496,0.5698689,0.4269368,0.0006750374],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000003559038,0.0002352768,0.8406423,0.0000863973,0.002323918,0.0008551557,0.04650442,0.0007809352,0.108568],"genre_scores_gemma":[0.00002508952,0.001184102,0.73756,0.0003263319,0.00172809,0.00006230067,0.001509806,0.00115159,0.2564527],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.227474,"threshold_uncertainty_score":0.9993012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4334047673219784,"score_gpt":0.5261208180433039,"score_spread":0.09271605072132555,"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."}}