{"id":"W2890986727","doi":"10.23889/ijpds.v3i4.963","title":"Using Artificial Intelligence Technology for Social Determinants and Risk Factors Surveillance","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Social determinants of health; Population; Health equity; Population health; Disease; Risk factor; Disease surveillance; Environmental health; Business; Psychology; Medicine; Public health; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006864161,0.0009744444,0.001134574,0.004308348,0.000633675,0.004371,0.001164395,0.00153826,0.004103983],"category_scores_gemma":[0.02085305,0.0003825819,0.001478904,0.003300804,0.001121193,0.002589671,0.002228164,0.002253541,0.001270165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001285659,"about_ca_system_score_gemma":0.001495141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005095504,"about_ca_topic_score_gemma":0.003177873,"domain_scores_codex":[0.9954214,0.002890404,0.0002533243,0.0005790144,0.000736845,0.0001189533],"domain_scores_gemma":[0.9852706,0.01161413,0.000811632,0.00114901,0.0009732129,0.0001813652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001372692,0.0004693234,0.03947885,0.0007839158,0.0007809095,0.0002383387,0.0005326493,0.07778395,0.001339504,0.08298109,0.02564325,0.769831],"study_design_scores_gemma":[0.00004768373,0.0001230022,0.01274486,0.0004865525,0.0001502836,0.0001458589,0.0004369315,0.6691157,0.001715412,0.277419,0.03751113,0.0001036388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01880908,0.006010594,0.9417821,0.00933174,0.0008854118,0.0005623242,0.002482717,0.002490385,0.01764572],"genre_scores_gemma":[0.3260017,0.008119875,0.6502539,0.002832694,0.001310065,0.001267962,0.003804863,0.0002068123,0.006202162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006864161,"threshold_uncertainty_score":0.03630161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3233185548000539,"score_gpt":0.531245212581993,"score_spread":0.207926657781939,"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."}}