{"id":"W2120827434","doi":"10.1186/1478-7954-8-3","title":"Statistical modeling of volume of alcohol exposure for epidemiological studies of population health: the US example","year":2010,"lang":"en","type":"article","venue":"Population Health Metrics","topic":"Alcohol Consumption and Health Effects","field":"Medicine","cited_by":209,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute on Alcohol Abuse and Alcoholism; Centre for Addiction and Mental Health","keywords":"Per capita; Medicine; Consumption (sociology); Epidemiology; Environmental health; Population; Gamma distribution; Demography; Econometrics; Statistics; Public health; Population health; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01218968,0.001057628,0.0009289972,0.001758534,0.00052495,0.001369896,0.001759524,0.001494813,0.00228134],"category_scores_gemma":[0.03218606,0.0004251476,0.002277818,0.002758935,0.0008914851,0.001192488,0.001305702,0.001787787,0.0003590531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002043545,"about_ca_system_score_gemma":0.001684595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02191342,"about_ca_topic_score_gemma":0.01298706,"domain_scores_codex":[0.9931319,0.005858528,0.0001396254,0.000344009,0.0003798374,0.0001460991],"domain_scores_gemma":[0.9741692,0.02261273,0.001181515,0.0008797422,0.001016817,0.0001399247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001352623,0.0000960352,0.01933032,0.0002383868,0.0003892512,0.0004928328,0.0005629224,0.7739952,0.0004232918,0.1581694,0.003726206,0.04244089],"study_design_scores_gemma":[0.00002941753,0.00008972596,0.002676535,0.00008635242,0.00008962249,0.0002295986,0.0001240834,0.8785402,0.0001581172,0.1135255,0.004416958,0.00003390305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05788289,0.002103343,0.9299365,0.003598891,0.0001818272,0.0002989854,0.001037139,0.0003159874,0.004644317],"genre_scores_gemma":[0.719511,0.004753804,0.2665673,0.0007130172,0.0003642566,0.001360828,0.001114289,0.0001361654,0.005479281],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02191342,"threshold_uncertainty_score":0.064466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4592808901567468,"score_gpt":0.516331037816502,"score_spread":0.05705014765975519,"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."}}