{"id":"W29510972","doi":"10.2196/rehab.8003","title":"“確認不足,思い込み”によるミスの防止にむけて","year":2006,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005605245,0.0003918398,0.0005986617,0.00058027,0.001006998,0.00119598,0.0005955501,0.001838757,0.05213487],"category_scores_gemma":[0.009601623,0.0002245885,0.0005956077,0.0003749261,0.002466671,0.001475345,0.0007741628,0.002335578,0.01360064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008604118,"about_ca_system_score_gemma":0.00238455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00157669,"about_ca_topic_score_gemma":0.004032311,"domain_scores_codex":[0.9976141,0.00104,0.0001869617,0.0002946981,0.0006959651,0.0001682588],"domain_scores_gemma":[0.9973556,0.001333222,0.000290143,0.0002276082,0.0006166528,0.0001767489],"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":[0.002132496,0.0006783922,0.003575806,0.002107064,0.0001479231,0.001292981,0.001183576,0.0003174788,0.009957849,0.07654896,0.216344,0.6857134],"study_design_scores_gemma":[0.001455593,0.002269239,0.0186993,0.002373332,0.0003982379,0.006911144,0.001489875,0.001092097,0.02313437,0.0882039,0.8537943,0.0001786419],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06506852,0.04282423,0.05004624,0.08399901,0.009132872,0.001900671,0.003621262,0.0009023377,0.7425048],"genre_scores_gemma":[0.6687024,0.02799951,0.07932393,0.04127529,0.005745513,0.005350414,0.00356724,0.0003813075,0.1676544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05213487,"threshold_uncertainty_score":0.1744085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01984398879445369,"score_gpt":0.2289381605528734,"score_spread":0.2090941717584197,"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."}}