{"id":"W2097025153","doi":"","title":"INFERENCE FOR INDIVIDUAL-LEVEL MODELS OF INFECTIOUS DISEASES IN LARGE POPULATIONS.","year":2010,"lang":"en","type":"article","venue":"PubMed","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Markov chain Monte Carlo; Inference; Computer science; Bayesian inference; Bayesian probability; Context (archaeology); Infectious disease (medical specialty); Missing data; Machine learning; Econometrics; Data mining; Artificial intelligence; Mathematics; Disease; Medicine; Geography","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":[0.01539858,0.0007604249,0.001730673,0.002090668,0.0007857958,0.002354093,0.00254863,0.00199433,0.004004348],"category_scores_gemma":[0.07379716,0.0009969177,0.002161314,0.001947477,0.001735188,0.003599428,0.002263475,0.003315754,0.0008198856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001516719,"about_ca_system_score_gemma":0.001828412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01072023,"about_ca_topic_score_gemma":0.0145855,"domain_scores_codex":[0.9942536,0.003979147,0.0002458389,0.000830548,0.0005268116,0.0001640526],"domain_scores_gemma":[0.9437583,0.04981953,0.002863958,0.002281574,0.0007165481,0.0005601753],"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":[0.0001530486,0.0001673096,0.02341688,0.0003698939,0.0007640427,0.0003482191,0.0007740146,0.728131,0.001092233,0.1693213,0.004579474,0.07088254],"study_design_scores_gemma":[0.00002979266,0.00003186641,0.001849181,0.00004051724,0.00005938346,0.0001139493,0.00006256777,0.8422788,0.0001556597,0.1536378,0.001716327,0.00002411906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01297253,0.0003626898,0.9847885,0.0004215385,0.00003383922,0.00004846681,0.0005142431,0.0002625889,0.0005955833],"genre_scores_gemma":[0.40706,0.001280418,0.5832716,0.000636481,0.0002312205,0.0005511526,0.003258532,0.0001904482,0.003520104],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01539858,"threshold_uncertainty_score":0.08143646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288887857793057,"score_gpt":0.2797814636938759,"score_spread":0.1508926779145701,"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."}}