{"id":"W4401666385","doi":"10.2196/58977","title":"Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Pharmacist; Breast cancer; Docetaxel; Adverse effect; Cancer; Natural language processing; Computer science; Internal medicine; Pharmacy; Family medicine","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":[0.002858778,0.0005081301,0.0005203256,0.00253806,0.0003964812,0.000618937,0.000454764,0.0005637119,0.0009479807],"category_scores_gemma":[0.009165806,0.0003908244,0.0004733925,0.001227184,0.0004139918,0.0006444302,0.0006504959,0.0002912023,0.0006751328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005272502,"about_ca_system_score_gemma":0.0005169294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004164638,"about_ca_topic_score_gemma":0.003725708,"domain_scores_codex":[0.998015,0.0005595866,0.0003901865,0.0005728874,0.0003644836,0.00009773096],"domain_scores_gemma":[0.9918099,0.002532365,0.001382818,0.0009910661,0.002847926,0.0004359824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002565393,0.0002630571,0.9781457,0.0001130052,0.00009096439,0.0008769273,0.0007848718,0.0001727713,0.002249114,0.00001674176,0.0003591442,0.01667115],"study_design_scores_gemma":[0.00005877876,0.001202333,0.9869423,0.00002616795,0.0002744985,0.002916626,0.0009657434,0.00334968,0.00267568,0.00003150139,0.001522267,0.00003441028],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969671,0.0002697971,0.001577311,0.00001992369,0.000007681583,0.0001226324,0.0007523061,0.00004425136,0.0002388292],"genre_scores_gemma":[0.9938734,0.0002758314,0.002906488,0.00005119637,0.00002535857,0.0001587714,0.002391982,0.00002141228,0.0002955973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004164638,"threshold_uncertainty_score":0.01511884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487692354388505,"score_gpt":0.3548497065304286,"score_spread":0.3399727829865436,"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."}}