{"id":"W2596180820","doi":"","title":"骨髄腫病勢評価のための検査：M蛋白，FLC評価からclonal change評価法まで","year":2015,"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":"Geography","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":[0.0007337724,0.0004070632,0.0004552367,0.0002116515,0.0001036862,0.00002725093,0.0006190588,0.0004481871,0.003317531],"category_scores_gemma":[0.0002040546,0.0004096062,0.0001173419,0.0003619131,0.0003613087,0.0002555178,0.0001451499,0.0009822436,0.002175638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001365009,"about_ca_system_score_gemma":0.0001713969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007204535,"about_ca_topic_score_gemma":0.00002637585,"domain_scores_codex":[0.9976944,0.00009318093,0.000448086,0.0004077181,0.0005756828,0.0007809409],"domain_scores_gemma":[0.9986665,0.00009693804,0.00005885987,0.0004728517,0.00008690414,0.0006179645],"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":[0.0002561117,0.0004487681,0.001123459,0.0008612702,0.001151947,0.001648024,0.01388181,0.0006798562,0.002465552,0.03217469,0.8859603,0.05934815],"study_design_scores_gemma":[0.005451831,0.0005216151,0.0006783858,0.0003375745,0.0004174247,0.0004376903,0.00531179,0.03991179,0.00492176,0.02550645,0.9148586,0.001645073],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1517584,0.1147387,0.001497151,0.01648991,0.01555512,0.0009317796,0.000285031,0.003329258,0.6954147],"genre_scores_gemma":[0.9930909,0.002502668,0.0006927839,0.0004596354,0.001522383,0.00005522677,0.00005915531,0.00006342546,0.001553829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8413324,"threshold_uncertainty_score":0.9998356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04105983073113203,"score_gpt":0.2773943056891999,"score_spread":0.2363344749580678,"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."}}