{"id":"W2737530890","doi":"","title":"CD30抗体医薬 ブレンツキシマブ・ベドチン","year":2013,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":1,"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002183009,0.0003386917,0.0003641349,0.000152842,0.0001279029,0.00003685401,0.0005420246,0.0003785081,0.02676394],"category_scores_gemma":[0.0001022716,0.0003268525,0.0001138228,0.0002601099,0.0003021907,0.0003530745,0.00009604192,0.0009108852,0.00813571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004853106,"about_ca_system_score_gemma":0.0000504752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001778607,"about_ca_topic_score_gemma":0.000007967071,"domain_scores_codex":[0.9981954,0.00005085875,0.0004277942,0.0003365108,0.0003014546,0.0006879592],"domain_scores_gemma":[0.9990168,0.0001149387,0.000042655,0.0004781139,0.00005271411,0.0002947594],"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":[0.00002774605,0.0003093873,0.001173681,0.001266097,0.00102167,0.0003507218,0.003978875,0.0003689642,0.02031768,0.02541959,0.7957874,0.1499782],"study_design_scores_gemma":[0.006501179,0.0006576295,0.01132345,0.0009318587,0.0007407495,0.0004021607,0.007229201,0.1388833,0.02256936,0.07592636,0.7311721,0.00366268],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3888857,0.04423433,0.0009023325,0.01201151,0.006098995,0.001055045,0.00004974334,0.002511756,0.5442506],"genre_scores_gemma":[0.9931158,0.003425775,0.0005269877,0.0004380611,0.0005173826,0.0001023787,0.00001703437,0.00004817753,0.001808446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.60423,"threshold_uncertainty_score":0.9999183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01424867859901438,"score_gpt":0.2450607712919612,"score_spread":0.2308120926929468,"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."}}