{"id":"W2742467018","doi":"","title":"学会TOPICS 第100回 米国胸部疾患学会COPDと酸化ストレス","year":2005,"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":"COPD; Computer science; Medicine; Internal 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":[0.0002810719,0.0003362723,0.0003541136,0.0001465505,0.0001376626,0.00002302551,0.0005347317,0.000403226,0.007501823],"category_scores_gemma":[0.00007671228,0.000345285,0.0001204934,0.0002469135,0.0002539449,0.0002721824,0.00008734904,0.0009906689,0.002046572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009249046,"about_ca_system_score_gemma":0.0000686977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002191056,"about_ca_topic_score_gemma":0.0000291897,"domain_scores_codex":[0.9981923,0.00004704857,0.0004533238,0.0003335869,0.0003142385,0.0006595002],"domain_scores_gemma":[0.9991255,0.00008584592,0.00004429562,0.0004619476,0.00003380175,0.000248608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008475808,0.0004781981,0.0009907456,0.001062458,0.001056698,0.0005027134,0.006977546,0.002821242,0.007024286,0.07811416,0.4237243,0.4771629],"study_design_scores_gemma":[0.001412102,0.00008652197,0.0004682447,0.0001324504,0.0001528831,0.00008499349,0.0005764649,0.03653673,0.006738966,0.003334897,0.9498497,0.0006259996],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2069778,0.08409768,0.001680681,0.03178508,0.005981922,0.0006358132,0.00009810112,0.002937664,0.6658052],"genre_scores_gemma":[0.9863969,0.007022433,0.001612694,0.0006893126,0.001706682,0.00002452813,0.00002003833,0.00004548798,0.002481903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7794191,"threshold_uncertainty_score":0.9998999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0162643741476968,"score_gpt":0.2616886548226566,"score_spread":0.2454242806749598,"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."}}