{"id":"W2746647970","doi":"","title":"遺伝性白室脳症（HDLS）と多発性硬化症の鑑別","year":2014,"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":[0.000558978,0.0003450925,0.000403089,0.0001556828,0.0001481756,0.00002289295,0.0005767893,0.0003866483,0.004101005],"category_scores_gemma":[0.000213828,0.000344706,0.0001162536,0.0002510915,0.0003193434,0.0001722112,0.00009101604,0.0009236193,0.001878124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004603232,"about_ca_system_score_gemma":0.00004493015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003115194,"about_ca_topic_score_gemma":0.00001199498,"domain_scores_codex":[0.9981371,0.00009499779,0.0004144679,0.0003673655,0.0003230425,0.0006630651],"domain_scores_gemma":[0.9989247,0.0001849983,0.00004809371,0.0005349508,0.00003398724,0.0002732202],"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":[0.0001665116,0.0004995864,0.00181668,0.002489718,0.001536878,0.0004485967,0.006303176,0.002858764,0.01480959,0.2114999,0.4310334,0.3265372],"study_design_scores_gemma":[0.002573299,0.00030094,0.001126016,0.0003159537,0.0002892394,0.0001149646,0.0007935124,0.1448254,0.0067072,0.02095521,0.8208904,0.001107886],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1304032,0.02470499,0.009244741,0.007650709,0.008107591,0.0004854435,0.00005411147,0.002851022,0.8164982],"genre_scores_gemma":[0.9947098,0.002420897,0.0005598249,0.0004701356,0.0008541624,0.00002660693,0.00001844114,0.00005083008,0.0008892235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8643067,"threshold_uncertainty_score":0.9999005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336018377594647,"score_gpt":0.2487507868395274,"score_spread":0.2353906030635809,"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."}}