{"id":"W2966486428","doi":"","title":"一目でわかるクリニカルレシピ：「CAR-T細胞療法の食事」","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":[0.0004029924,0.0003743366,0.0003882231,0.0001832415,0.0002270465,0.00002635806,0.0006434313,0.0004329713,0.01274415],"category_scores_gemma":[0.0001343977,0.0003756852,0.0001200848,0.0003793587,0.0008822427,0.0002162985,0.0001235265,0.0008425498,0.004076438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006307635,"about_ca_system_score_gemma":0.00008475329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005030609,"about_ca_topic_score_gemma":0.00003462521,"domain_scores_codex":[0.9979429,0.00006595017,0.0004444584,0.0004205157,0.0003539474,0.0007721756],"domain_scores_gemma":[0.9988995,0.0001038156,0.00005052709,0.0005791327,0.00007862548,0.0002884257],"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":[0.0002619782,0.0004642823,0.001551285,0.001249486,0.001982164,0.0009452394,0.01337953,0.0001048463,0.02898818,0.08547993,0.7192689,0.1463242],"study_design_scores_gemma":[0.003128906,0.0007104053,0.001621057,0.0004361838,0.0004502135,0.000247551,0.002298327,0.03545609,0.03039977,0.02057316,0.9031082,0.001570129],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2077943,0.022725,0.002220752,0.005405329,0.01075023,0.0005140287,0.0001020279,0.002482638,0.7480057],"genre_scores_gemma":[0.9931094,0.002299825,0.000745958,0.0004596068,0.002153347,0.00002539039,0.0000178978,0.00005692906,0.00113164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7853151,"threshold_uncertainty_score":0.9998695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742130469609386,"score_gpt":0.2662422923256976,"score_spread":0.2488209876296037,"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."}}