{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001026858,0.002754444,0.002082471,0.003260388,0.0007016483,0.0026436,0.003398367,0.002425245,0.1657417],"category_scores_gemma":[0.005428483,0.001090659,0.001309129,0.006429903,0.0004973317,0.001312856,0.001907829,0.001585577,0.2376468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001098136,"about_ca_system_score_gemma":0.001906517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03703195,"about_ca_topic_score_gemma":0.05174856,"domain_scores_codex":[0.9991033,0.0001730664,0.00008098688,0.0003003179,0.000172569,0.0001697338],"domain_scores_gemma":[0.9987512,0.0003216671,0.0001387622,0.0003043616,0.0002980415,0.0001861194],"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":[0.00004719486,0.0000131944,0.0003744421,0.0003241675,0.00002706005,0.000007737019,0.00001038804,0.0002555109,0.00004725981,0.0002370403,0.9974113,0.001244776],"study_design_scores_gemma":[0.0005865131,0.00003104376,0.003537479,0.0002844438,0.00004130968,0.00003778518,0.00005895624,0.000917065,0.0002593793,0.001585309,0.9926279,0.00003278037],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004404858,0.00002538581,0.00004057469,0.00002911864,0.00001279244,0.00000464324,0.9991819,0.0003158672,0.0003456867],"genre_scores_gemma":[0.0002048181,0.00002915986,0.0001376655,0.00002835958,0.000006659945,0.00003634909,0.9989135,0.0001053016,0.0005380904],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8342583,"threshold_uncertainty_score":0.5544612,"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."}}