{"id":"W3202602851","doi":"10.3390/genes12101523","title":"Silver: Forging almost Gold Standard Datasets","year":2021,"lang":"en","type":"article","venue":"Genes","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; McGill University Health Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Forging; Gold standard (test); Metallurgy; Biology; Computational biology; Computer science; Engineering drawing; Materials science; Engineering; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00009706314,0.0001010006,0.00009886105,0.00001141225,0.00006249465,0.00004062933,0.0001231395,0.00008908091,0.00005168565],"category_scores_gemma":[0.000014399,0.00009857577,0.00005696202,0.0000532716,0.00002738686,0.000003085184,0.0001903413,0.0000482724,0.00002361872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007068761,"about_ca_system_score_gemma":0.00007814313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003856902,"about_ca_topic_score_gemma":0.00004621375,"domain_scores_codex":[0.9993594,0.00001474495,0.0001487621,0.0001870563,0.00008142427,0.0002086184],"domain_scores_gemma":[0.999465,0.000004720308,0.00004189596,0.0003767963,0.00004739922,0.00006415483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007693945,0.0000384558,0.001649727,0.00006313731,0.0001605835,0.0000389558,0.00007916701,0.0003691165,0.5809605,0.000596912,0.2547927,0.1611738],"study_design_scores_gemma":[0.0002822099,0.00004526933,0.000135382,0.000007911145,0.00001291976,0.00003952029,0.00009954361,0.0002058179,0.1660418,0.0001638372,0.8328098,0.0001559216],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8908876,0.03989332,0.03630828,0.001513118,0.002106685,0.0004574479,0.003324748,0.00007511117,0.02543371],"genre_scores_gemma":[0.9717433,0.002632662,0.01095688,0.002399866,0.001109041,0.00001652328,0.007307168,0.00004709805,0.003787474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5780172,"threshold_uncertainty_score":0.4019803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00808249348705134,"score_gpt":0.2357437485469919,"score_spread":0.2276612550599406,"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."}}