{"id":"W1569042123","doi":"10.1111/j.1360-0443.2006.01536.x","title":"RISK CURVES: GAMBLING WITH DATA","year":2006,"lang":"en","type":"letter","venue":"Addiction","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Lottery; Psychology; Proxy (statistics); Measure (data warehouse); Social psychology; Econometrics; Statistics; Computer science; Economics; Mathematics; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001405508,0.0003048334,0.0002680558,0.0001715107,0.0001262517,0.00004189425,0.0003737963,0.0005647317,0.001185307],"category_scores_gemma":[0.000007956571,0.0002523914,0.00005835602,0.0001887305,0.00004850966,0.0001323666,0.00005558395,0.001316535,0.001130847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006127379,"about_ca_system_score_gemma":0.00003032178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003061744,"about_ca_topic_score_gemma":0.0001035039,"domain_scores_codex":[0.9981321,0.0001424267,0.0002434155,0.0007896976,0.000337968,0.0003544263],"domain_scores_gemma":[0.997867,0.00007425692,0.000281406,0.001690772,0.00005558232,0.00003098837],"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":[0.00001268038,0.00008354163,0.01599999,0.00001888341,0.0002661627,0.0004206866,0.00002234967,0.000001152715,3.70718e-7,0.000001209783,0.9783271,0.004845894],"study_design_scores_gemma":[0.0007665221,0.0001483812,0.04330402,0.0002845593,0.001601924,0.00006903781,0.000006898095,0.000005316407,0.000002223876,0.00001449414,0.9535135,0.0002831121],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.06475563,0.03706585,0.009281637,0.5102061,0.0386764,0.008087224,0.04737845,0.006409212,0.2781395],"genre_scores_gemma":[0.04829587,0.001055284,0.001594287,0.5032773,0.01770952,0.0007334802,0.3009818,0.0008269358,0.1255255],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2536034,"threshold_uncertainty_score":0.9999928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1323685077365755,"score_gpt":0.3795902351436689,"score_spread":0.2472217274070933,"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."}}