{"id":"W2348599607","doi":"10.3138/jmvfh.3587","title":"Screening questions to identify Canadian Veterans","year":2016,"lang":"en","type":"article","venue":"Journal of Military Veteran and Family Health","topic":"Agriculture and Farm Safety","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Veterans Affairs Canada","funders":"Queen's University; Canadian Defence Academy; U.S. Department of Veterans Affairs","keywords":"Navy; Military service; Legislation; Military personnel; Population; Veterans Affairs; Mental health; Medicine; Service (business); Service member; Gerontology; Political science; Operations research; Law; Psychiatry; Environmental health; Engineering; Business","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.004798654,0.00063068,0.0003836877,0.003877742,0.004359405,0.001267321,0.001621072,0.0007778844,0.01685805],"category_scores_gemma":[0.01830595,0.0003492959,0.0008390381,0.003164514,0.0007939311,0.0009818274,0.002112731,0.000810043,0.002930974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01907338,"about_ca_system_score_gemma":0.05276893,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8534325,"about_ca_topic_score_gemma":0.906718,"domain_scores_codex":[0.9968483,0.0004676687,0.0004632643,0.0002104756,0.001241372,0.0007690203],"domain_scores_gemma":[0.9840854,0.001372553,0.0009607175,0.0004407869,0.01208315,0.001057356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003591697,0.0003632732,0.3543868,0.001636583,0.00007215657,0.00072771,0.02574501,0.0007560888,0.001674281,0.009397237,0.3530544,0.2518272],"study_design_scores_gemma":[0.0001078417,0.0001888254,0.5460995,0.001709235,0.00007875147,0.0005627812,0.02473641,0.001082984,0.001859543,0.002574094,0.4208387,0.0001612533],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5702882,0.003467384,0.01384918,0.02207728,0.001108049,0.02542169,0.1190934,0.001082601,0.2436121],"genre_scores_gemma":[0.7625604,0.005902699,0.08168801,0.007564676,0.0002203921,0.02159339,0.06218023,0.0001587296,0.05813149],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1465675,"threshold_uncertainty_score":0.2948612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03400162869472193,"score_gpt":0.2836518030479883,"score_spread":0.2496501743532664,"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."}}