{"id":"W2073808979","doi":"10.1515/cclm.2011.610","title":"Towards more complete specifications for acceptable analytical performance – a plea for error grid analysis","year":2011,"lang":"en","type":"article","venue":"Clinical Chemistry and Laboratory Medicine (CCLM)","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health; Alberta Health Services","funders":"","keywords":"Computer science; Grid; Data mining; Harm; Protocol (science); Type I and type II errors; Reliability engineering; Set (abstract data type); Error detection and correction; Observational error; Risk analysis (engineering); Algorithm; Statistics; Medicine; Mathematics; Engineering; Pathology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2469034,0.003109277,0.003767371,0.004697438,0.002247211,0.01417544,0.01006961,0.007362145,0.004161038],"category_scores_gemma":[0.3702148,0.002287169,0.00394831,0.003585369,0.006887638,0.01751505,0.007265216,0.01071609,0.003752876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0054968,"about_ca_system_score_gemma":0.01212276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006131269,"about_ca_topic_score_gemma":0.002749271,"domain_scores_codex":[0.7144846,0.1586971,0.03514154,0.009547587,0.07855027,0.003579002],"domain_scores_gemma":[0.3874123,0.3049046,0.0328637,0.1068192,0.1657057,0.002294515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004070036,0.0004759766,0.007179713,0.002596763,0.0003519908,0.000391241,0.002381796,0.1370884,0.008006922,0.6239093,0.033503,0.183708],"study_design_scores_gemma":[0.0001300629,0.0008968332,0.003463231,0.00464977,0.0001512468,0.0005478024,0.001602472,0.1432305,0.02065806,0.6974763,0.1265477,0.0006461113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.003903089,0.002029379,0.9749795,0.007731814,0.000545923,0.0003552351,0.0004478925,0.001213078,0.00879402],"genre_scores_gemma":[0.08135571,0.001658576,0.9074359,0.00346909,0.0005057714,0.00134878,0.001120306,0.0009077144,0.002198269],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.2469034,"threshold_uncertainty_score":0.9287021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3623482017219636,"score_gpt":0.4534082255197949,"score_spread":0.09106002379783129,"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."}}