{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009494341,0.002612342,0.002527439,0.002474341,0.0006061083,0.004681456,0.003318038,0.00335262,0.01647813],"category_scores_gemma":[0.03014002,0.0003754347,0.001397581,0.002715946,0.001863255,0.003930817,0.00265325,0.003833822,0.01113231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001935268,"about_ca_system_score_gemma":0.001917059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009854157,"about_ca_topic_score_gemma":0.0004177618,"domain_scores_codex":[0.9894624,0.004334618,0.0008145268,0.001305705,0.003526119,0.0005565872],"domain_scores_gemma":[0.9879515,0.007657064,0.0007436617,0.001344999,0.001917497,0.0003853615],"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":[0.0007794931,0.0004180463,0.002299204,0.001099969,0.0003793389,0.0004225395,0.00007910064,0.2550682,0.002551121,0.1375967,0.1009322,0.4983742],"study_design_scores_gemma":[0.0001182413,0.0006118744,0.00124839,0.000701167,0.0002120709,0.001037732,0.00007851391,0.698761,0.003962268,0.2156908,0.07747575,0.0001022851],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004649493,0.005002174,0.9720783,0.002128016,0.0009113224,0.0002504299,0.001343857,0.001452023,0.01218436],"genre_scores_gemma":[0.4177708,0.01354739,0.4670755,0.005153774,0.003796402,0.002598434,0.01056708,0.00200255,0.07748805],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01647813,"threshold_uncertainty_score":0.05512482,"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."}}