{"id":"W2966869854","doi":"10.1016/j.clinbiochem.2019.08.002","title":"Autoverification of test results in the core clinical laboratory","year":2019,"lang":"en","type":"review","venue":"Clinical Biochemistry","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Test (biology); Audit; Quality assurance; Protocol (science); Quality (philosophy); Process (computing); Consistency (knowledge bases); Reliability engineering; Acceptance testing; Software engineering; Medicine; Artificial intelligence; Operations management; External quality assessment; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.007172408,0.001225768,0.003510856,0.00527718,0.0002795196,0.002243415,0.002706588,0.001463704,0.003322306],"category_scores_gemma":[0.01447485,0.0005654675,0.002053296,0.004087189,0.001163667,0.002002016,0.001175471,0.001987521,0.001520115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325469,"about_ca_system_score_gemma":0.003290704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002866806,"about_ca_topic_score_gemma":0.003473148,"domain_scores_codex":[0.9946609,0.00159111,0.001213978,0.0007511384,0.001638114,0.0001448072],"domain_scores_gemma":[0.9817058,0.01212769,0.002713095,0.000626752,0.002636622,0.0001900235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000133755,0.00004486133,0.0006948772,0.04252857,0.0003330425,0.0001120917,0.00005918878,0.0001417876,0.0006361555,0.0009961358,0.009432822,0.9448867],"study_design_scores_gemma":[0.0002071891,0.0004393099,0.01339776,0.08977272,0.003248647,0.004684256,0.0002458647,0.0004401547,0.003888542,0.00291771,0.8806227,0.000135119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001753945,0.9982989,0.0004711653,0.0002117817,0.0002621363,0.00001667539,0.00004568461,0.00001355345,0.000504784],"genre_scores_gemma":[0.002350797,0.9946235,0.001301012,0.0007092939,0.0004257685,0.00002807849,0.0001785655,0.000008245281,0.0003746965],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007172408,"threshold_uncertainty_score":0.03793174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3900048873336002,"score_gpt":0.5632143744575318,"score_spread":0.1732094871239315,"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."}}