{"id":"W2050440632","doi":"10.1159/000050731","title":"Steps towards Constructing a Global Comparative Risk Analysis for Alcohol Consumption: Determining Indicators and Empirical Weights for Patterns of Drinking, Deciding about Theoretical Minimum, and Dealing with Different Consequences","year":2001,"lang":"en","type":"article","venue":"European Addiction Research","topic":"Alcohol Consumption and Health Effects","field":"Medicine","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Bundesamt für Gesundheit; World Health Organization","keywords":"Consumption (sociology); Coronary heart disease; Alcohol; Alcohol consumption; Environmental health; Set (abstract data type); Heavy drinking; Psychology; Human factors and ergonomics; Medicine; Demography; Poison control; Gerontology; Computer science; Cardiology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.001719837,0.0001917992,0.0005332936,0.0005030869,0.0005365889,0.00007308937,0.00007796325,0.00007351859,0.0001152034],"category_scores_gemma":[0.0003361083,0.0001437,0.00008875184,0.0003452118,0.001190391,0.00006011054,0.00007329207,0.0003265042,0.00000168081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008691892,"about_ca_system_score_gemma":0.0001057535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001862313,"about_ca_topic_score_gemma":0.00004430314,"domain_scores_codex":[0.9974537,0.0006794076,0.0004890171,0.0004919177,0.0004681114,0.0004177729],"domain_scores_gemma":[0.9973779,0.001530121,0.0002494284,0.0001717455,0.000306077,0.0003646876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001172112,0.00004701978,0.9783545,0.0001567903,0.0005372138,0.00002606938,0.0008708491,0.000003105847,0.00008204769,0.002458989,0.00002627999,0.01626507],"study_design_scores_gemma":[0.004092514,0.001211534,0.9850172,0.0005554424,0.0007423435,0.0002030497,0.00135357,0.005409839,0.0004358017,0.00008040236,0.0007246258,0.000173665],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779887,0.0006284721,0.01940492,0.0001892559,0.00003917255,0.001120474,0.00009352754,0.00004402268,0.0004914916],"genre_scores_gemma":[0.9963874,0.0006893429,0.002590782,0.0001044183,0.00009084291,0.00006042827,0.00004294151,0.00001833736,0.00001554066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0183987,"threshold_uncertainty_score":0.5859917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2243394738135975,"score_gpt":0.4724541306911925,"score_spread":0.248114656877595,"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."}}