{"id":"W2903438333","doi":"","title":"南方熊楠から学ぶ日本人の心 第3回：熊楠の落斯馬（ロスマ）論争と私のCETP論争","year":2018,"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":[0.000528832,0.0004928716,0.0005114487,0.0002471405,0.0003018192,0.00003548984,0.0008634122,0.0005620067,0.0143131],"category_scores_gemma":[0.0001987061,0.0004910104,0.0001570059,0.0004873934,0.001087495,0.0002867287,0.0001721597,0.001108193,0.004641674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000849549,"about_ca_system_score_gemma":0.0001147287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000744921,"about_ca_topic_score_gemma":0.00004684385,"domain_scores_codex":[0.9973196,0.00008769464,0.0005888919,0.000556534,0.0004589013,0.0009883912],"domain_scores_gemma":[0.9985536,0.000139321,0.00007279455,0.0007626712,0.0001054223,0.0003661621],"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":[0.0002784007,0.0005624191,0.001867744,0.001409139,0.001915223,0.001043002,0.01170376,0.0001031041,0.01859191,0.05522517,0.7619217,0.1453785],"study_design_scores_gemma":[0.003699628,0.00084161,0.002088939,0.0005488205,0.0005085431,0.0002718027,0.002243683,0.02939204,0.02757954,0.01929729,0.9116768,0.001851309],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2034109,0.03147255,0.002148998,0.006768418,0.01315698,0.0006960649,0.0001410917,0.003175403,0.7390296],"genre_scores_gemma":[0.9903176,0.003822812,0.0007745093,0.0005922422,0.002499731,0.00003645871,0.00002504346,0.00007815098,0.001853386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7869068,"threshold_uncertainty_score":0.9997541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01800171146873313,"score_gpt":0.2677879136210337,"score_spread":0.2497862021523006,"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."}}