{"id":"W3132270960","doi":"10.1093/clinchem/hvab008","title":"Development and Validation of Measurement Traceability for In Situ Immunoassays","year":2021,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Health Authority","funders":"National Center for Advancing Translational Sciences; National Cancer Institute; National Institutes of Health","keywords":"Traceability; Analyte; Gold standard (test); Quality assurance; NIST; Standardization; Computer science; External quality assessment; Immunoassay; Data mining; Mathematics; Pathology; Medicine; Chromatography; Statistics; Chemistry; Software 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000436606,0.00005548176,0.0001063127,0.000002678469,0.00002126305,0.00000343253,0.00004392088,0.0001121355,0.000001331733],"category_scores_gemma":[0.000397574,0.00005754269,0.00004408864,0.00003079482,0.00005292232,0.000001038376,0.00004952228,0.00004976601,9.777771e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001301731,"about_ca_system_score_gemma":0.00009709538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.394619e-7,"about_ca_topic_score_gemma":0.00000377322,"domain_scores_codex":[0.9993111,0.00001302482,0.0003226352,0.0002256811,0.00005648845,0.00007110013],"domain_scores_gemma":[0.9995365,0.00002264615,0.00007091981,0.0001970707,0.0001450412,0.00002787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002371247,0.0001365769,0.002186531,0.00005168147,0.000008761514,2.059288e-7,0.000005409504,9.190388e-7,0.9912329,0.00001400928,0.00007363987,0.006265595],"study_design_scores_gemma":[0.0002914969,0.00001537755,0.002044649,0.00001803434,0.000005119471,0.000001708098,0.00002756039,0.000006039157,0.9831563,0.0002710461,0.01409816,0.00006449975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995379,0.0001922688,0.003931228,0.0001320042,0.00001180159,0.0001012361,0.000004492687,0.000007567932,0.0002404454],"genre_scores_gemma":[0.9531438,0.00005432039,0.04658739,0.00002568258,0.00003254206,0.00002354196,0.00007559179,0.000004909538,0.00005217368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04265616,"threshold_uncertainty_score":0.2346523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06873678292303945,"score_gpt":0.3642390036614839,"score_spread":0.2955022207384445,"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."}}