{"id":"W2561698232","doi":"","title":"神経内科におけるてんかん診療； てんかん診療へのさらなる参画，新規抗てんかん薬の使い方","year":2011,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"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":[0.001357907,0.0002144644,0.0001746487,0.0006992352,0.00217348,0.003708001,0.0003680677,0.001012203,0.01360324],"category_scores_gemma":[0.002598173,0.0001960411,0.0001993004,0.0004271902,0.005200882,0.001972394,0.0007541289,0.001353229,0.00364309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002300443,"about_ca_system_score_gemma":0.003114277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006117302,"about_ca_topic_score_gemma":0.004604685,"domain_scores_codex":[0.9991915,0.0001347709,0.00003980566,0.000148505,0.0003976421,0.00008784032],"domain_scores_gemma":[0.9986236,0.0003679896,0.0001310032,0.0001433675,0.0005798644,0.0001542073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004914337,0.00006429377,0.001811448,0.00009915105,0.00001678638,0.0001911599,0.002477219,0.0005091532,0.004970212,0.9056541,0.008071274,0.07608604],"study_design_scores_gemma":[0.00002765448,0.0001907612,0.00877832,0.0001625522,0.00005474037,0.0006330418,0.00541164,0.001373609,0.02141885,0.4552805,0.5065942,0.00007409621],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06942664,0.004292739,0.0283805,0.01232352,0.001126586,0.000125797,0.00014592,0.0001211217,0.8840572],"genre_scores_gemma":[0.7511426,0.003121088,0.01653518,0.002397525,0.0005276022,0.0000841803,0.00007832479,0.00004852021,0.226065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01360324,"threshold_uncertainty_score":0.04550737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03041070002375282,"score_gpt":0.251507951290536,"score_spread":0.2210972512667832,"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."}}