{"id":"W2740913050","doi":"","title":"レニン・アンジオテンシン・アルドステロン系の最新知見；L.Gabliel Navar先生を囲んで","year":2009,"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":[0.000462024,0.0005595472,0.0006013229,0.0003027779,0.0002310475,0.00004685933,0.0008544471,0.000617255,0.006198087],"category_scores_gemma":[0.0001558626,0.0005729825,0.0002011141,0.0005635869,0.0002967526,0.0003687562,0.00007168348,0.001511839,0.001832261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009491463,"about_ca_system_score_gemma":0.0001131498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000296588,"about_ca_topic_score_gemma":0.000006914281,"domain_scores_codex":[0.9971346,0.00008211637,0.0006651217,0.0005653994,0.0005083517,0.001044362],"domain_scores_gemma":[0.998673,0.0001349224,0.00007890601,0.000720276,0.00006094438,0.0003319218],"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":[0.0002595277,0.0009304913,0.0003682101,0.0008029164,0.001043639,0.001943452,0.005674694,0.001297288,0.02172994,0.1158502,0.547721,0.3023787],"study_design_scores_gemma":[0.008380903,0.001679683,0.006585328,0.001118707,0.0009940016,0.0007627368,0.003536502,0.06216877,0.02122557,0.1141737,0.7752548,0.004119312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1371069,0.07028563,0.002031309,0.0190603,0.006310095,0.0008752394,0.0001315491,0.00389935,0.7602996],"genre_scores_gemma":[0.9882656,0.006964032,0.0007381235,0.001414293,0.0008973111,0.00002064803,0.00004108022,0.00005047291,0.001608477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8511586,"threshold_uncertainty_score":0.9996722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482104930356494,"score_gpt":0.2590147240171243,"score_spread":0.2441936747135594,"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."}}