{"id":"W3112645506","doi":"","title":"書評：対談 風の彼方へ 禅と武士道の生き方","year":2019,"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":[0.000334305,0.0003219268,0.0004241697,0.0001576537,0.0000763709,0.0000194738,0.0004862082,0.0003854814,0.01856373],"category_scores_gemma":[0.00005499633,0.0003189343,0.0001270821,0.0002603157,0.0001745613,0.0002178871,0.00009725254,0.0009730558,0.007498531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000574924,"about_ca_system_score_gemma":0.00007071673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003824514,"about_ca_topic_score_gemma":0.000007947351,"domain_scores_codex":[0.9982299,0.00004898979,0.0003960849,0.0003750508,0.0003247977,0.000625241],"domain_scores_gemma":[0.9990532,0.0001165331,0.00004618645,0.0005484644,0.00003115618,0.000204458],"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":[0.0004672511,0.000935616,0.0204087,0.007418129,0.004007846,0.001610523,0.01566861,0.00396187,0.08703077,0.142073,0.5648873,0.1515304],"study_design_scores_gemma":[0.005884456,0.0005357983,0.004506799,0.0007825663,0.0004388416,0.000223632,0.003832657,0.07058272,0.01600792,0.01572382,0.8793837,0.00209714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4608234,0.0251479,0.0002139762,0.003090868,0.006708823,0.0005186754,0.00005644179,0.001269427,0.5021705],"genre_scores_gemma":[0.992432,0.003285354,0.0002366907,0.0003118854,0.0004058534,0.00002067382,0.00002225349,0.00004819782,0.003237107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5316086,"threshold_uncertainty_score":0.9999263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01259332538108858,"score_gpt":0.2483700062124085,"score_spread":0.2357766808313199,"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."}}