{"id":"W2134646536","doi":"10.1002/sim.2899","title":"Bayesian modelling of tuberculosis clustering from DNA fingerprint data","year":2007,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal General Hospital; McGill University","funders":"","keywords":"Genotyping; Bayesian probability; Cluster analysis; Categorical variable; Bayes' theorem; Computer science; Statistics; Data mining; Computational biology; Genetics; Biology; Artificial intelligence; Genotype; Mathematics; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00260571,0.0001700033,0.0007208132,0.0003077516,0.00003335826,0.000002803161,0.0003100905,0.0001250082,0.0004195484],"category_scores_gemma":[0.003083227,0.0001388394,0.00002483733,0.0002720788,0.000283139,0.00004958415,0.0002449865,0.0004714371,0.0000106423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001024099,"about_ca_system_score_gemma":0.00007278162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005805056,"about_ca_topic_score_gemma":0.001708301,"domain_scores_codex":[0.9975623,0.00009449432,0.0009105755,0.0004480559,0.0004742449,0.0005102531],"domain_scores_gemma":[0.9967384,0.001822878,0.0001268335,0.0009106182,0.0001204937,0.0002808098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005192745,0.00135555,0.4656436,0.00262021,0.001670327,0.003834352,0.008198781,0.01625349,0.04473322,0.01142769,0.06913205,0.369938],"study_design_scores_gemma":[0.002808772,0.000525779,0.07806955,0.001013468,0.0001841976,0.00003537214,0.000752702,0.9058144,0.0006404198,0.007811984,0.002117152,0.0002262166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05475659,0.0005954866,0.9393051,0.002127702,0.0002076887,0.0002476291,0.0003078571,0.00002222496,0.002429759],"genre_scores_gemma":[0.834835,0.0008825338,0.16242,0.0006290524,0.0003525018,0.000003305554,0.0008073487,0.00002524721,0.00004502208],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8895609,"threshold_uncertainty_score":0.8775547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1008636724832523,"score_gpt":0.3940453108420791,"score_spread":0.2931816383588268,"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."}}