{"id":"W6926016393","doi":"10.22008/fk2/cs5lka/srqadd","title":"w50z10bw6.rtl","year":2021,"lang":"bpy","type":"dataset","venue":"Geological Survey of Denmark and Greenland (GEUS)","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apotex Pharmachem (Canada)","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002690205,0.0007964983,0.002180601,0.0002479439,0.000297827,0.00007700788,0.000371144,0.0014796,0.004706158],"category_scores_gemma":[0.003008636,0.0006192416,0.0003513276,0.0008540619,0.0006747608,0.00007672449,0.0006159815,0.001405076,0.0002573225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007200631,"about_ca_system_score_gemma":0.0003126681,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01804388,"about_ca_topic_score_gemma":0.01183016,"domain_scores_codex":[0.994312,0.001512299,0.001137138,0.001341281,0.00083501,0.0008623015],"domain_scores_gemma":[0.9952499,0.002030767,0.0005893793,0.0009094748,0.0006042879,0.0006162085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01410131,0.0006501523,0.5118946,0.001072801,0.0008185703,0.0007327861,0.00005290816,0.00001001757,0.00004012601,0.000004657907,0.4250942,0.04552788],"study_design_scores_gemma":[0.002320567,0.005584936,0.8522054,0.0005536078,0.0005280874,0.0003298959,0.00005084576,0.0001312701,0.0000639376,0.00006586487,0.1374981,0.000667536],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5299057,0.02990101,0.000326715,0.0004079341,0.001920303,0.0008149096,0.4355165,0.00006070147,0.001146148],"genre_scores_gemma":[0.5148985,0.01224517,0.0002238712,0.0005300681,0.0009798773,0.00004484994,0.4685302,0.00004396474,0.002503485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3403108,"threshold_uncertainty_score":0.9998167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04184742454767008,"score_gpt":0.2864519279248947,"score_spread":0.2446045033772246,"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."}}