{"id":"W2744208825","doi":"","title":"小児科領域におけるてんかん診療；個々の患者の「ライフステージ」に沿った治療戦略を考える","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":[0.001106559,0.0002159725,0.0002052978,0.0006029828,0.001840756,0.002441619,0.0003450923,0.0007815798,0.01395228],"category_scores_gemma":[0.002261545,0.0001986879,0.0002355658,0.0003257124,0.003272768,0.00142689,0.0006386245,0.001096171,0.003811935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001452712,"about_ca_system_score_gemma":0.002235139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004796376,"about_ca_topic_score_gemma":0.003880536,"domain_scores_codex":[0.9992786,0.00009935597,0.0000389677,0.0001427115,0.0003518492,0.00008846718],"domain_scores_gemma":[0.9984797,0.0004082617,0.0001541901,0.000159024,0.000631666,0.0001672342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002277407,0.0002488042,0.01009117,0.0003636396,0.0000695259,0.0007659488,0.004480137,0.001522758,0.04107287,0.671405,0.01709562,0.2526568],"study_design_scores_gemma":[0.00005334358,0.0005567723,0.03229262,0.0002367948,0.000151046,0.002174061,0.007481634,0.00296801,0.1172446,0.2974111,0.539284,0.0001459719],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1658784,0.00471638,0.04218702,0.008825344,0.001196309,0.0001739864,0.0002800679,0.0002291769,0.7765134],"genre_scores_gemma":[0.8073609,0.002815646,0.01922695,0.001832003,0.0005301185,0.00008297132,0.0001308044,0.00006241722,0.1679582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01395228,"threshold_uncertainty_score":0.04667503,"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."}}