{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009560229,0.0009314616,0.001863378,0.00204998,0.0007009626,0.002397342,0.002901716,0.002615557,0.002004725],"category_scores_gemma":[0.03019687,0.001399308,0.001560582,0.001726133,0.001933719,0.002076637,0.001585455,0.002065522,0.0006379174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002759374,"about_ca_system_score_gemma":0.001277674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03648159,"about_ca_topic_score_gemma":0.02074741,"domain_scores_codex":[0.9973869,0.001276049,0.0001058713,0.0005469203,0.0003931643,0.0002910961],"domain_scores_gemma":[0.9838171,0.01230253,0.001724009,0.0005922115,0.001114913,0.0004492832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001966652,0.00006309606,0.009695933,0.000113743,0.0001190347,0.000188275,0.0004139105,0.928238,0.0009883015,0.04085912,0.0009442596,0.01817959],"study_design_scores_gemma":[0.00001366058,0.00001509543,0.001435445,0.00001877855,0.00001084851,0.00002812514,0.00001764054,0.9855785,0.00008950784,0.0124465,0.0003230668,0.00002278499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1612053,0.001197779,0.8312564,0.001343162,0.00007093869,0.0002306912,0.001171959,0.0005087271,0.00301499],"genre_scores_gemma":[0.868133,0.001237827,0.1198919,0.0002611204,0.0001208573,0.0005089053,0.001640442,0.0001817698,0.00802409],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03648159,"threshold_uncertainty_score":0.0725385,"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."}}