{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.002896525,0.0002557778,0.001087322,0.000007301488,0.00004777394,0.0000339061,0.0003883128,0.001872832,0.0004965035],"category_scores_gemma":[0.01448806,0.0001581229,0.0006169106,0.00009216973,0.0006031193,0.0000291675,0.000146844,0.004758618,0.0001225108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003366801,"about_ca_system_score_gemma":0.0007412604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002457998,"about_ca_topic_score_gemma":3.801737e-7,"domain_scores_codex":[0.9965422,0.0002457304,0.001815918,0.0004569644,0.0006272279,0.0003119736],"domain_scores_gemma":[0.9915093,0.005035852,0.001089143,0.001439722,0.0006889988,0.0002370343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000381917,0.0001205423,0.001712774,0.000254318,0.0002660613,0.000156676,0.000007484441,1.328848e-8,0.00003141551,0.000002360443,0.9954962,0.001570211],"study_design_scores_gemma":[0.001384052,0.000224933,0.0001873213,0.0001520701,0.0003920559,0.00001763218,0.00004559089,0.000005264592,0.0000888328,0.0001129063,0.9972264,0.0001629448],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01603823,0.001459718,0.00000229991,0.9585633,0.0008998384,0.0002584576,0.0001092867,0.00004323124,0.0226257],"genre_scores_gemma":[0.01796323,0.0003349383,0.00009318798,0.9227172,0.01318634,0.00002094408,0.0002306599,0.00008522555,0.04536829],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03584606,"threshold_uncertainty_score":0.999423,"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."}}