{"id":"W2108268423","doi":"10.1002/sim.745","title":"Logistic discrimination of mixtures of M. tuberculosis and non‐specific tuberculin reactions","year":2001,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"International Union Against Tuberculosis and Lung Disease","keywords":"Homogeneity (statistics); Tuberculin; Tuberculosis; Logistic regression; Goodness of fit; Tuberculin test; Medicine; Statistics; Mathematics; 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":[],"consensus_categories":[],"category_scores_codex":[0.01257695,0.0009800354,0.001441092,0.002822229,0.0004587139,0.001803183,0.001596961,0.001316027,0.001581651],"category_scores_gemma":[0.05610555,0.001145043,0.001444828,0.001351248,0.001379144,0.001896294,0.00229552,0.001538692,0.0006694666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006353541,"about_ca_system_score_gemma":0.0004733724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099984,"about_ca_topic_score_gemma":0.001104351,"domain_scores_codex":[0.9952742,0.003056907,0.0002450505,0.0006107532,0.0005266275,0.0002864237],"domain_scores_gemma":[0.9585288,0.03496301,0.003471548,0.001618236,0.001007636,0.0004108359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.005270719,0.0004267963,0.3409592,0.0006073602,0.001036982,0.002177683,0.001894436,0.2219593,0.01635052,0.0598064,0.003020245,0.3464903],"study_design_scores_gemma":[0.00007023806,0.0001418162,0.03004052,0.00004204439,0.0001156619,0.001105159,0.0001506164,0.9242947,0.002678794,0.04023002,0.001033097,0.00009749069],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4094882,0.0008657936,0.5868266,0.0003681718,0.00006348448,0.0001429183,0.0001759795,0.000616014,0.001452934],"genre_scores_gemma":[0.9323055,0.0003771521,0.06547045,0.00005824611,0.00006588634,0.0001036062,0.000398139,0.00006446667,0.001156539],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01257695,"threshold_uncertainty_score":0.06651407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422861188760234,"score_gpt":0.3286785300077517,"score_spread":0.2944499181201493,"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."}}