{"id":"W4391967899","doi":"10.2196/52566","title":"AI Analysis of General Medicine in Japan: Present and Future Considerations","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Healthcare cost, quality, practices","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Engineering ethics; Medicine; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005812493,0.0004930278,0.0003605835,0.004812474,0.001373036,0.005196732,0.001103829,0.001066484,0.00430743],"category_scores_gemma":[0.0103668,0.0001947248,0.0004746706,0.004576872,0.002456648,0.004477162,0.001072723,0.001301459,0.0002348119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007752727,"about_ca_system_score_gemma":0.004538628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03209286,"about_ca_topic_score_gemma":0.05265655,"domain_scores_codex":[0.9978071,0.001191176,0.0001668787,0.0001713836,0.0004942386,0.0001692094],"domain_scores_gemma":[0.989742,0.004294041,0.001642933,0.0004549,0.003273892,0.0005921787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003907016,0.0003530825,0.1958173,0.005276316,0.0002185488,0.003490038,0.04743527,0.003734188,0.003926833,0.1034218,0.03626349,0.5996724],"study_design_scores_gemma":[0.00004399197,0.0004177222,0.3811831,0.004817085,0.0004018234,0.003215567,0.2085559,0.01692479,0.002628414,0.1104948,0.2710516,0.0002652046],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3700308,0.1467821,0.02237312,0.324604,0.002565342,0.0002169299,0.00128366,0.0003914043,0.1317526],"genre_scores_gemma":[0.931977,0.03366331,0.01947208,0.008162982,0.00186557,0.000105711,0.0003636723,0.0000489731,0.004340639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03209286,"threshold_uncertainty_score":0.06381214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6118346457466433,"score_gpt":0.6674025218323101,"score_spread":0.05556787608566682,"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."}}