{"id":"W2932613184","doi":"10.3389/fendo.2019.00185","title":"Artificial Intelligence and Machine Learning in Endocrinology and Metabolism: The Dawn of a New Era","year":2019,"lang":"en","type":"article","venue":"Frontiers in Endocrinology","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institutes of Health","keywords":"Endocrinology; Internal medicine; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0001997816,0.00014362,0.0004701616,0.000396773,0.00004405222,0.000008133753,0.0001122247,0.0001054078,0.00007128593],"category_scores_gemma":[0.0003296,0.000115691,0.00003184698,0.0002998906,0.0002928196,0.0000708712,0.00008365943,0.000680434,0.00001118434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004482057,"about_ca_system_score_gemma":0.0001617742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003714946,"about_ca_topic_score_gemma":0.0007450558,"domain_scores_codex":[0.9983954,0.0001526345,0.0005533626,0.0003343998,0.00009749414,0.0004666458],"domain_scores_gemma":[0.9993399,0.000205258,0.0001121987,0.0002239604,0.00004253622,0.00007616396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002388943,0.00005424391,0.5492228,0.00004890461,0.00002048707,0.00002012313,0.003145585,0.00008325431,0.0003810159,0.005680831,0.0001199284,0.4409839],"study_design_scores_gemma":[0.0008891588,0.002181515,0.6501663,0.0003380498,0.000229398,0.001458048,0.05211092,0.02632772,0.07204423,0.1387372,0.05462086,0.0008965645],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789565,0.009808194,0.001700301,0.007526472,0.00111601,0.0004927582,0.00000153333,0.00002040236,0.0003778409],"genre_scores_gemma":[0.9934841,0.003439973,0.002285286,0.0003239836,0.0001132577,0.00001922935,0.000006305786,0.00001318832,0.0003146665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4400873,"threshold_uncertainty_score":0.5615913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08239219369568819,"score_gpt":0.3463550974480517,"score_spread":0.2639629037523635,"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."}}