{"id":"W2946016028","doi":"10.1177/0840470419848428","title":"A population health perspective on artificial intelligence","year":2019,"lang":"en","type":"article","venue":"Healthcare Management Forum","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Public Health Ontario; University of Toronto; Institute of Population and Public Health; McGill University","funders":"","keywords":"Perspective (graphical); Population; Computer science; Data science; Psychology; Artificial intelligence; Medicine; Environmental health","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001546961,0.0004072476,0.0006286902,0.0005552645,0.00160074,0.00002978462,0.0004631788,0.0002930993,0.001255814],"category_scores_gemma":[0.0001151512,0.0004020567,0.0001589887,0.0008571696,0.00005567318,0.0002195906,0.0002638477,0.00127236,0.01069546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003248879,"about_ca_system_score_gemma":0.0003029505,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02607039,"about_ca_topic_score_gemma":0.01556746,"domain_scores_codex":[0.9934666,0.001096202,0.001612243,0.001085985,0.0008644869,0.001874521],"domain_scores_gemma":[0.9969706,0.0004244774,0.0006540973,0.001094567,0.0003994749,0.0004568101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002295239,0.000102859,0.06765914,0.0009277039,0.00002753477,0.000007996444,0.003074489,0.0001604736,0.000001118882,0.846368,0.003231203,0.07820994],"study_design_scores_gemma":[0.0003120941,0.002558547,0.05337411,0.002783609,0.00002424628,0.000003358313,0.3940919,0.007229178,0.00004783492,0.4875023,0.05090716,0.001165678],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2351861,0.001237681,0.005073865,0.6267936,0.01256104,0.02495807,0.0001372697,0.001894608,0.0921578],"genre_scores_gemma":[0.9611986,0.0002508763,0.0007246279,0.03399399,0.0004006753,0.0004441717,0.00009106946,0.00008935123,0.002806675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7260125,"threshold_uncertainty_score":0.9998431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1224110034490879,"score_gpt":0.48208000227081,"score_spread":0.3596689988217222,"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."}}