{"id":"W2747626091","doi":"","title":"新規分子標的薬剤・支持療法の外来導入：アプレピタント","year":2010,"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000433536,0.0003609009,0.0003657645,0.0001750921,0.0001666379,0.00002903611,0.0006970682,0.0005759042,0.01288767],"category_scores_gemma":[0.0002018385,0.0003624055,0.0001286693,0.0002895671,0.0004523955,0.0002116598,0.0001095841,0.00241964,0.001764597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002369598,"about_ca_system_score_gemma":0.00009211587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000500012,"about_ca_topic_score_gemma":0.00007192428,"domain_scores_codex":[0.9981242,0.00003806032,0.0004198785,0.0003849046,0.0003381644,0.0006947521],"domain_scores_gemma":[0.9988264,0.0001410235,0.00004683202,0.000622048,0.00004465293,0.0003189931],"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":[0.0001361337,0.000625796,0.002473333,0.001510701,0.001474066,0.001664559,0.006605039,0.0002352911,0.2573619,0.1557782,0.4028278,0.1693071],"study_design_scores_gemma":[0.002651603,0.0001836559,0.002195773,0.0001658369,0.0003476794,0.0003578829,0.001168111,0.02587266,0.02679682,0.01891219,0.9199444,0.001403382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5268375,0.01005555,0.0004196089,0.007723982,0.01462996,0.000455934,0.0001004136,0.002298019,0.437479],"genre_scores_gemma":[0.9947854,0.001721574,0.0008947398,0.000318795,0.001076831,0.0000339664,0.00002191584,0.00005653802,0.001090248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5171166,"threshold_uncertainty_score":0.9998828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242620742157547,"score_gpt":0.2551619172801331,"score_spread":0.2427357098585576,"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."}}