{"id":"W2176987742","doi":"10.1002/bimj.201700101","title":"Bivariate random‐effects meta‐analysis models for diagnostic test accuracy studies using arcsine‐based transformations","year":2018,"lang":"en","type":"article","venue":"Biometrical Journal","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Bivariate analysis; Statistics; Bivariate data; Mathematics; Random effects model; Sensitivity (control systems); Gold standard (test); Meta-analysis; Computer science; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.1240934,0.003408111,0.005748993,0.005486222,0.0006605926,0.002937195,0.005319966,0.002776372,0.00727512],"category_scores_gemma":[0.1988026,0.001411495,0.01852201,0.00595862,0.001767959,0.002836549,0.002440489,0.005076597,0.0009519182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0018858,"about_ca_system_score_gemma":0.002446796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003955655,"about_ca_topic_score_gemma":0.003446803,"domain_scores_codex":[0.9013399,0.08513376,0.003811199,0.006270889,0.002980532,0.0004638376],"domain_scores_gemma":[0.8393709,0.1438639,0.005174296,0.008928292,0.002392786,0.0002698361],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.005966694,0.000346501,0.02467638,0.0186753,0.1173815,0.0008892349,0.0009249027,0.4100337,0.001978424,0.1154667,0.01309396,0.2905667],"study_design_scores_gemma":[0.002872346,0.0014566,0.008534838,0.002357116,0.07126351,0.0005100184,0.0001614876,0.693027,0.002869785,0.1941907,0.02246858,0.0002880189],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006595049,0.01323279,0.974345,0.001043669,0.0003675105,0.001498131,0.001535736,0.0008524536,0.000529613],"genre_scores_gemma":[0.2900036,0.009839745,0.6767507,0.001405519,0.0004078978,0.01507393,0.002841348,0.0004271816,0.003250056],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8759066,"threshold_uncertainty_score":0.6562766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3701916153503816,"score_gpt":0.4866135381563493,"score_spread":0.1164219228059677,"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."}}