{"id":"W6986289512","doi":"","title":"Performance measures. 2019: Quarter 4 (2019: Oct. 1 - 2019: Dec. 31)","year":2017,"lang":"en","type":"article","venue":"State Elections Enforcement Commission (State of Connecticut)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Index (typography); Head (geology); Table (database)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006902962,0.0004031942,0.0003732823,0.0001913232,0.001121897,0.0001732161,0.0007573955,0.0001438647,0.0002557373],"category_scores_gemma":[0.000421196,0.0003668817,0.000182137,0.0001263823,0.0002353474,0.00006896121,0.0002483847,0.000320612,0.00009285141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007136181,"about_ca_system_score_gemma":0.0002922892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003219488,"about_ca_topic_score_gemma":0.000139263,"domain_scores_codex":[0.9975904,0.0001025355,0.0007964702,0.0004125899,0.0004862025,0.0006117548],"domain_scores_gemma":[0.9969472,0.00004841508,0.000804172,0.001466853,0.0004717552,0.0002615541],"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":[0.001524729,0.0005227841,0.01493644,0.0003384487,0.000866176,0.000007586039,0.001338458,0.01866353,0.1479174,0.0005118751,0.7095652,0.1038073],"study_design_scores_gemma":[0.002466238,0.002130555,0.00876368,0.0001525493,0.00009683922,0.00006164838,0.0001224809,0.01134887,0.156375,0.0002212672,0.8173899,0.0008709632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7643672,0.0006046778,0.04383182,0.001126524,0.002036423,0.001592099,0.0001997772,0.0001858331,0.1860557],"genre_scores_gemma":[0.9537917,0.00101768,0.001368577,0.0001316501,0.000110017,0.00003517896,0.0002458697,0.00005312345,0.04324625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1894245,"threshold_uncertainty_score":0.9998783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009917048694765526,"score_gpt":0.2713052200192377,"score_spread":0.2613881713244722,"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."}}