{"id":"W2094034311","doi":"10.1016/j.clinbiochem.2005.11.003","title":"Interference of Accel® wipes with LifeScan SureStep® Flexx glucose meters","year":2005,"lang":"en","type":"article","venue":"Clinical Biochemistry","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; Calgary Laboratory Services","funders":"","keywords":"Chemistry; Computer science; Mathematics","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":[0.007352238,0.001842633,0.001214041,0.001404325,0.0009166769,0.001579043,0.001161405,0.001493255,0.004671113],"category_scores_gemma":[0.01877713,0.001351826,0.001123719,0.001130391,0.0008701932,0.0005267584,0.001721306,0.001051235,0.001921705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005480913,"about_ca_system_score_gemma":0.001368229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003435316,"about_ca_topic_score_gemma":0.00292733,"domain_scores_codex":[0.9849257,0.005520707,0.0009260415,0.001617608,0.00587251,0.001137545],"domain_scores_gemma":[0.983605,0.01056158,0.00102196,0.001239149,0.003251059,0.0003212723],"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":[0.004522272,0.0005547738,0.05155617,0.00170701,0.0006587489,0.001552393,0.002242544,0.001544089,0.8227762,0.00139505,0.004756548,0.1067342],"study_design_scores_gemma":[0.0001044886,0.002144053,0.04456215,0.0003492257,0.0005858425,0.002060932,0.0008092319,0.008173442,0.9285133,0.0006068549,0.01203991,0.00005058658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7272643,0.01528424,0.2313307,0.002032008,0.00270925,0.00100352,0.000715091,0.001453375,0.01820748],"genre_scores_gemma":[0.8782919,0.003935125,0.09893824,0.003453893,0.0004708203,0.0004020198,0.001151722,0.0005307962,0.01282549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007352238,"threshold_uncertainty_score":0.03888279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06887702455972684,"score_gpt":0.4160875769591244,"score_spread":0.3472105523993976,"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."}}