{"id":"W2716646616","doi":"10.1186/s12917-017-1103-7","title":"Descriptive and network analyses of the equine contact network at an equestrian show in Ontario, Canada and implications for disease spread","year":2017,"lang":"en","type":"article","venue":"BMC Veterinary Research","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Population; Veterinary medicine; Horse; Disease; Equine influenza; Medicine; Geography; Demography; Family medicine; Environmental health; Biology; Pathology; Vaccination","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006566319,0.00008427063,0.0001708033,0.000007490994,0.0007750803,0.00005451688,0.0003423369,0.00003384735,0.00004349274],"category_scores_gemma":[0.0001839578,0.00003401533,0.00003752408,0.00007571032,0.0001989987,0.0001069139,0.0005680737,0.00009076814,1.741856e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009324969,"about_ca_system_score_gemma":0.00008123576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8322023,"about_ca_topic_score_gemma":0.9931893,"domain_scores_codex":[0.9988282,0.0002791061,0.0001528065,0.0002678838,0.00009741314,0.000374625],"domain_scores_gemma":[0.9990991,0.0004454305,0.00007688181,0.0001581945,0.00005322478,0.0001671208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006193973,0.00002040536,0.9922975,0.00001325365,0.00001105503,0.00000335509,0.00001130031,0.00002181043,0.003448026,0.0007003775,0.001663777,0.001189801],"study_design_scores_gemma":[0.000133455,0.0006012294,0.9942766,0.00002842748,0.00001296484,0.000001086458,0.00004826163,0.0003541405,0.000001991571,0.002170664,0.002303899,0.00006732462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976972,0.0002960715,0.000002870643,0.001198477,0.00003453621,0.0004718461,0.00006080182,0.000003650031,0.0002345468],"genre_scores_gemma":[0.99922,0.00004424667,0.00005539602,0.00005375587,0.0001151624,0.00007639459,0.000041927,9.832299e-7,0.0003921431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1609871,"threshold_uncertainty_score":0.596137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4528967271525375,"score_gpt":0.4231585356973981,"score_spread":0.0297381914551394,"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."}}