{"id":"W2911835721","doi":"10.2196/12100","title":"Artificial Intelligence in Clinical Health Care Applications: Viewpoint","year":2019,"lang":"en","type":"article","venue":"Interactive Journal of Medical Research","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Applications of artificial intelligence; Health care; Domain (mathematical analysis); Computer science; Data science; Mathematics; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01284594,0.0001093552,0.0005655069,0.0007211383,0.00007049844,0.00003460576,0.0004343442,0.0002446265,0.001641515],"category_scores_gemma":[0.007757762,0.00008514897,0.0001922001,0.0007981165,0.0002542066,0.0001774497,0.0000994701,0.003627772,0.0006967543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008567157,"about_ca_system_score_gemma":0.004757423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004878903,"about_ca_topic_score_gemma":0.0002271783,"domain_scores_codex":[0.9934697,0.0009906528,0.002276541,0.0002856168,0.002500981,0.0004765245],"domain_scores_gemma":[0.9928771,0.003585819,0.0004199636,0.0003165707,0.002010857,0.0007897426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008339432,0.0008130067,0.01000321,0.0001940153,0.00002749234,0.00006250964,0.003406747,0.000003768156,0.0000324986,0.001465373,0.001029357,0.9821281],"study_design_scores_gemma":[0.0009313541,0.03609833,0.06111871,0.02102842,0.00007253866,0.002287937,0.4207484,0.007225932,0.01743193,0.07061698,0.361495,0.0009444303],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8510541,0.005937167,0.01015852,0.1267133,0.002048033,0.001947411,0.000003011727,0.00001437126,0.002124044],"genre_scores_gemma":[0.9931214,0.003008186,0.0006337304,0.001735109,0.001394094,0.00003319835,0.000004564412,0.00001589606,0.00005380858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9811836,"threshold_uncertainty_score":0.9992711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4293089720191041,"score_gpt":0.6653346802255904,"score_spread":0.2360257082064863,"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."}}