{"id":"W2967582854","doi":"","title":"南方熊楠から学ぶ日本人の心 第１回：「熊楠のプロフィールと学問の基本概念」","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":"Geography","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":[0.0004373305,0.0004175309,0.0004282504,0.0002100816,0.0002325136,0.00002568957,0.0007290247,0.0004734902,0.01267182],"category_scores_gemma":[0.0001611066,0.0004184342,0.0001314059,0.0004308749,0.000977488,0.0002442726,0.0001396266,0.0009160657,0.004324494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007117694,"about_ca_system_score_gemma":0.00009168261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005125374,"about_ca_topic_score_gemma":0.00003786133,"domain_scores_codex":[0.997725,0.00006896157,0.0004998264,0.0004723444,0.0003924597,0.0008414722],"domain_scores_gemma":[0.9987618,0.0001234225,0.00005812947,0.000641765,0.00009134874,0.0003235427],"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":[0.0002281362,0.0004174876,0.0009948196,0.001002475,0.001485849,0.0007456535,0.009803047,0.00007319517,0.01921676,0.03870503,0.7713299,0.1559976],"study_design_scores_gemma":[0.003960478,0.0008883079,0.002595047,0.0005503016,0.0005029214,0.000288905,0.002287751,0.03720035,0.0412966,0.02177302,0.8867329,0.001923428],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1793841,0.03922402,0.001888474,0.006575431,0.01173916,0.0005967501,0.0001162281,0.002971198,0.7575046],"genre_scores_gemma":[0.9909099,0.003885835,0.0006310556,0.0005319216,0.002384477,0.0000291494,0.00001865756,0.00006623455,0.001542711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8115259,"threshold_uncertainty_score":0.9998267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772030216248074,"score_gpt":0.2674092177864826,"score_spread":0.2496889156240019,"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."}}