{"id":"W2016223478","doi":"10.1016/j.cll.2014.10.006","title":"Quality Control of Automated Cell Counters","year":2015,"lang":"en","type":"review","venue":"Clinics in Laboratory Medicine","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Blood Services; Health Sciences Centre; University of Alberta Hospital","funders":"","keywords":"Quality (philosophy); Computer science; Reliability engineering; Truncation (statistics); Control (management); Calibration; Medical physics; Hematology analyzer; Data mining; Medicine; Statistics; Mathematics; Internal medicine; Machine learning; Artificial intelligence; 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":[0.01675131,0.001678947,0.003860001,0.007757144,0.0004627551,0.00335665,0.003881089,0.002174659,0.003119132],"category_scores_gemma":[0.02478909,0.0007147898,0.002482205,0.005636091,0.001748998,0.002387852,0.001918915,0.001842696,0.0008258676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003435009,"about_ca_system_score_gemma":0.006775185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00858383,"about_ca_topic_score_gemma":0.006279542,"domain_scores_codex":[0.987598,0.003136714,0.00233345,0.001397533,0.005224056,0.0003102685],"domain_scores_gemma":[0.9707889,0.01636108,0.005428346,0.0007360027,0.006426719,0.0002591371],"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":[0.0001495447,0.00005414234,0.00118242,0.06403572,0.0004705265,0.00006621479,0.00009963345,0.0004391213,0.0006896181,0.002714506,0.008778512,0.9213201],"study_design_scores_gemma":[0.0001515944,0.0005130068,0.01093421,0.08657743,0.003916944,0.001493732,0.0003573237,0.001049568,0.006632689,0.004046078,0.8841478,0.0001796215],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001689234,0.9984251,0.0005678062,0.0002347484,0.0001425092,0.00002051541,0.00004465062,0.00001154149,0.0003842695],"genre_scores_gemma":[0.003328944,0.9933835,0.001987327,0.000516254,0.0002149819,0.00003540994,0.0001925773,0.000007129987,0.0003338433],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01675131,"threshold_uncertainty_score":0.08859044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1833677994739988,"score_gpt":0.523236362053521,"score_spread":0.3398685625795222,"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."}}