{"id":"W4398656049","doi":"10.7910/dvn/c6wcuy/tqr4jo","title":"MangerSattlerCPS_ReplicationCode.do","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001682385,0.0003240905,0.0002987898,0.0001057998,0.00006695359,0.00006019862,0.0005770111,0.0005164471,0.0005294543],"category_scores_gemma":[0.0001167931,0.0002996161,0.0001955535,0.0001140082,0.0001052245,0.000005002527,0.0004311153,0.0002222298,0.01612085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003181519,"about_ca_system_score_gemma":0.00008567632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002498023,"about_ca_topic_score_gemma":0.00002438964,"domain_scores_codex":[0.9984137,0.00005668208,0.0002653737,0.0007767794,0.0002245812,0.0002628235],"domain_scores_gemma":[0.9971038,0.0000109291,0.0002299699,0.00246215,0.0001084218,0.00008470164],"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":[0.00003358298,0.00004397001,0.000005587783,0.00003822001,0.0001095193,0.000006857199,7.469001e-7,0.000001789247,0.01036303,0.000001694736,0.9885393,0.0008556886],"study_design_scores_gemma":[0.0001408586,0.00008732611,0.000006941954,0.00003845918,0.0001327036,0.00001893588,0.00001068718,0.000003390016,0.01074537,0.000006114945,0.9884256,0.0003836865],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006165743,0.000008111847,0.0002269446,0.00000621917,0.000188832,0.0002230512,0.998928,0.00002978588,0.0003274412],"genre_scores_gemma":[0.0002277531,0.001680302,0.001337425,0.0004778809,0.0004190448,0.000016206,0.9943628,0.00002859732,0.001449983],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01559139,"threshold_uncertainty_score":0.9999456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411686836498525,"score_gpt":0.2793997627261176,"score_spread":0.2652828943611323,"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."}}