{"id":"W280973563","doi":"10.18907/jjsre.30.6_360","title":"肺癌におけるコンベックス式超音波気管支鏡ガイド下針生検(EBUS-TBNA)を用いた,縦隔・肺門リンパ節転移診断( 肺癌の縦隔リンパ節転移診断-画像と内視鏡的診断-)","year":2008,"lang":"ja","type":"article","venue":"気管支学 : 日本気管支研究会雑誌","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003268049,0.0003029855,0.000515302,0.00109318,0.001138645,0.003316003,0.0006481264,0.001128999,0.00765637],"category_scores_gemma":[0.003752047,0.0002981432,0.0003713536,0.0008912847,0.00202568,0.001980943,0.0008038898,0.001538859,0.002572162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001739904,"about_ca_system_score_gemma":0.001594526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001964725,"about_ca_topic_score_gemma":0.002152831,"domain_scores_codex":[0.9984945,0.0005310284,0.0001126902,0.0002809323,0.0004374156,0.0001433202],"domain_scores_gemma":[0.9989067,0.0004558855,0.0001313734,0.00008189135,0.0003069855,0.0001171797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001639034,0.0006171699,0.06216066,0.001877793,0.0003122672,0.00157334,0.003201861,0.0009771106,0.0842203,0.08551435,0.02034242,0.7375637],"study_design_scores_gemma":[0.0005843622,0.001769691,0.06525128,0.001209057,0.001206298,0.0179875,0.005406264,0.005139595,0.2730391,0.09921294,0.5289194,0.0002745111],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4406108,0.1475032,0.07134205,0.02455596,0.005293683,0.0009399502,0.001107391,0.000587191,0.3080598],"genre_scores_gemma":[0.8674465,0.01926419,0.05477591,0.006487673,0.001901204,0.000423821,0.0004076213,0.0001164711,0.04917667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00765637,"threshold_uncertainty_score":0.02561307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02541177819825432,"score_gpt":0.2842519325298543,"score_spread":0.2588401543316,"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."}}