{"id":"W3178878198","doi":"","title":"肺がん専門医インタビュー(5)：肺がんエキスパートドクターのEGFR陽性肺がん治療の考え方","year":2017,"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006858635,0.0002497687,0.0001975699,0.0006050314,0.001371104,0.00184203,0.0004268875,0.001017648,0.02623449],"category_scores_gemma":[0.001069938,0.0001825564,0.0003133313,0.0004327734,0.00170818,0.001153055,0.0006332256,0.0009319307,0.006985484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244426,"about_ca_system_score_gemma":0.001671783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005770502,"about_ca_topic_score_gemma":0.005137419,"domain_scores_codex":[0.9994912,0.00006615941,0.00003377971,0.0001064866,0.0002196065,0.00008266008],"domain_scores_gemma":[0.9994904,0.00008248362,0.00006891909,0.00004575057,0.0002556468,0.00005675319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002996429,0.0002430726,0.005830663,0.0006412362,0.00006805232,0.001138536,0.002030163,0.001750597,0.07454428,0.6486599,0.02626548,0.2385284],"study_design_scores_gemma":[0.00004006087,0.0004961554,0.01101937,0.0001983321,0.00009273775,0.001869948,0.00266922,0.002610358,0.1004101,0.1081641,0.7723123,0.0001172561],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1200226,0.007017181,0.04788354,0.007748608,0.002862704,0.0003401719,0.0006006766,0.000299347,0.8132253],"genre_scores_gemma":[0.6306688,0.00350508,0.02729485,0.002856877,0.0007541198,0.000172096,0.0003009419,0.00006281195,0.3343844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02623449,"threshold_uncertainty_score":0.08776307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02371757295023074,"score_gpt":0.2827882779115027,"score_spread":0.259070704961272,"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."}}