{"id":"W3034549135","doi":"","title":"大腸癌診療update 2016 抗血管新生薬のエビデンスupdate","year":2016,"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":[0.000463052,0.0004333488,0.0004354561,0.0002012641,0.0001386207,0.00001988995,0.0007300538,0.0003990012,0.01371495],"category_scores_gemma":[0.0001243708,0.0002973317,0.0001388039,0.0002369953,0.0005044004,0.0004261553,0.0001508636,0.0005138752,0.007533151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008357091,"about_ca_system_score_gemma":0.0001064339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002259402,"about_ca_topic_score_gemma":0.000008634489,"domain_scores_codex":[0.9976476,0.00008581823,0.0005376886,0.0004886473,0.0003471405,0.0008930827],"domain_scores_gemma":[0.9986823,0.0001743236,0.00007090944,0.0006755595,0.0000493118,0.0003475697],"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":[0.0001547375,0.0001785663,0.0005028197,0.0004166675,0.001012217,0.0006827546,0.0008430416,0.00002532901,0.05678019,0.03082696,0.6108686,0.2977081],"study_design_scores_gemma":[0.003765507,0.0001619076,0.0006377327,0.0008490957,0.0002462628,0.0001221771,0.0002581821,0.001375505,0.02930772,0.01805997,0.9440656,0.001150281],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1862843,0.07733884,0.01212222,0.0696471,0.01804291,0.001360722,0.001075667,0.006553207,0.627575],"genre_scores_gemma":[0.9702242,0.02305717,0.0003118767,0.0003787681,0.0006504384,0.00003800063,0.00001578576,0.00006884226,0.005254933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7839399,"threshold_uncertainty_score":0.9999479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01356512806519778,"score_gpt":0.2493475977870247,"score_spread":0.235782469721827,"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."}}