{"id":"W3142586679","doi":"","title":"フェンタニルクエン酸塩経皮吸収型製剤（一日型：フェントステープ）（総説）","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004159315,0.0004588943,0.0004737148,0.000230305,0.0001658729,0.00001666745,0.000820867,0.000502741,0.01923948],"category_scores_gemma":[0.0001076706,0.0004635386,0.0001641446,0.0003578661,0.0004659992,0.0002901564,0.0001381896,0.001153423,0.002342025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006164684,"about_ca_system_score_gemma":0.00009217508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001421055,"about_ca_topic_score_gemma":0.00002576603,"domain_scores_codex":[0.9976766,0.00007658657,0.0005588761,0.0004675903,0.0003685751,0.0008518499],"domain_scores_gemma":[0.9987785,0.00008580171,0.00006961845,0.0006554156,0.00005123989,0.0003593784],"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":[0.0007592526,0.001994836,0.006962366,0.003705098,0.004790249,0.005587303,0.05619937,0.0001599315,0.02334478,0.169174,0.5847532,0.1425696],"study_design_scores_gemma":[0.01296397,0.002081999,0.02333184,0.001720666,0.002491437,0.001182529,0.01208403,0.06851842,0.07877105,0.1114699,0.6778692,0.007514933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1182264,0.02777026,0.001105235,0.001082037,0.005721418,0.0004915586,0.00008489369,0.002163074,0.8433551],"genre_scores_gemma":[0.9926713,0.004112758,0.001093475,0.000311955,0.00046701,0.00004387648,0.00001775309,0.00007242782,0.001209417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8744449,"threshold_uncertainty_score":0.9997816,"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."}}