{"id":"W2978202251","doi":"","title":"血清学的診断（ASCA~ANCAを含めて）","year":2008,"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":"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000220055,0.0003403061,0.0003970584,0.0001631758,0.0002523511,0.000008528134,0.0005045399,0.0003717859,0.005244975],"category_scores_gemma":[0.00009132036,0.0003483434,0.0001347394,0.0003184196,0.000523524,0.0002025919,0.00007895211,0.0009674806,0.001664971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005413988,"about_ca_system_score_gemma":0.00009764812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005925414,"about_ca_topic_score_gemma":0.00001188079,"domain_scores_codex":[0.9981654,0.00005185441,0.0004181822,0.0003505803,0.0003531386,0.000660843],"domain_scores_gemma":[0.9990906,0.0001048754,0.0000426685,0.0004631493,0.00003659988,0.0002620738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001902916,0.0007482551,0.005800187,0.001463695,0.00181722,0.00688344,0.01504693,0.001180391,0.01050116,0.02000864,0.8781426,0.05821721],"study_design_scores_gemma":[0.006917454,0.0004948623,0.01256373,0.0005050012,0.0004850017,0.002575926,0.002255277,0.04072969,0.02015333,0.009503389,0.9011788,0.002637538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.532196,0.06031746,0.0009295848,0.003637199,0.004991591,0.0004186482,0.00007279582,0.002192225,0.3952444],"genre_scores_gemma":[0.9815028,0.01541694,0.0004179568,0.0002853048,0.0006303527,0.00002926979,0.00001935726,0.00004757975,0.001650434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4493068,"threshold_uncertainty_score":0.9998969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069765257850329,"score_gpt":0.250412336382534,"score_spread":0.2297146838040307,"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."}}