{"id":"W3152847844","doi":"10.1016/s2589-7500(21)00057-1","title":"Who does the model learn from?","year":2021,"lang":"en","type":"letter","venue":"The Lancet Digital Health","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Scopus; Medicine; Artificial intelligence; Transplantation; MEDLINE; Internal medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005646959,0.001525078,0.001964765,0.001313609,0.0006110458,0.00344145,0.002338916,0.00363879,0.01645698],"category_scores_gemma":[0.03457668,0.0006487608,0.001224472,0.00120565,0.001072451,0.006756961,0.001447421,0.004683169,0.006469341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308578,"about_ca_system_score_gemma":0.00193923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01131783,"about_ca_topic_score_gemma":0.008546666,"domain_scores_codex":[0.9971732,0.001553192,0.000123791,0.0006887249,0.0002412672,0.0002198312],"domain_scores_gemma":[0.9892899,0.008435303,0.0003547178,0.0008468892,0.0007476198,0.0003254794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008664893,0.0004216722,0.02984772,0.001510202,0.000763367,0.0007690152,0.0004218798,0.1519955,0.0006737423,0.0647736,0.1687789,0.579178],"study_design_scores_gemma":[0.0001247919,0.0001347763,0.002132739,0.0008307832,0.0001311396,0.0003043074,0.0003066799,0.7330397,0.000800407,0.2400507,0.0220644,0.00007953078],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.05241506,0.01901395,0.6825707,0.1875981,0.003159324,0.0004057291,0.01237387,0.003895031,0.03856818],"genre_scores_gemma":[0.8241344,0.01263354,0.1148283,0.01370599,0.003978626,0.0007034202,0.0102583,0.001094689,0.0186627],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.01645698,"threshold_uncertainty_score":0.05505413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05194977297370292,"score_gpt":0.3134808197677292,"score_spread":0.2615310467940263,"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."}}