{"id":"W2123556300","doi":"10.1373/clinchem.2015.243048","title":"The Power of Asterisks","year":2015,"lang":"en","type":"letter","venue":"Clinical Chemistry","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Protocol (science); Test (biology); Population; External quality assessment; Confidence interval; Medicine; Reference values; Statistics; Medical physics; Data collection; Consistency (knowledge bases); Computer science; Pathology; Environmental health; Mathematics; Biology; Internal medicine; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03031363,0.001368077,0.001630473,0.005818911,0.005780512,0.01424276,0.004986377,0.005103366,0.0970876],"category_scores_gemma":[0.2799546,0.0008625235,0.001382627,0.006939276,0.009779995,0.01113239,0.008605946,0.008779475,0.04442046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0036223,"about_ca_system_score_gemma":0.006309313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001873343,"about_ca_topic_score_gemma":0.001538086,"domain_scores_codex":[0.9428044,0.02607939,0.00612552,0.00808473,0.01425785,0.00264806],"domain_scores_gemma":[0.7166417,0.1723116,0.02193722,0.03790152,0.04523383,0.005974215],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006048639,0.0000418472,0.002236276,0.0008197204,0.00009947838,0.0007272873,0.002625844,0.0004992008,0.0003066178,0.3109587,0.5823601,0.09872022],"study_design_scores_gemma":[0.00004272399,0.00003778344,0.000875975,0.0009808159,0.00002331125,0.0004922221,0.00132373,0.0008436285,0.0004622021,0.07445417,0.9204248,0.00003872544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.009487237,0.009221524,0.09032652,0.2641101,0.2000785,0.0006216469,0.006601941,0.003763503,0.415789],"genre_scores_gemma":[0.3685142,0.01165251,0.1304132,0.1257274,0.1001069,0.001924711,0.008473889,0.00833383,0.2448535],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9696864,"threshold_uncertainty_score":0.3247904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1489555857949475,"score_gpt":0.4546353155460743,"score_spread":0.3056797297511268,"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."}}