{"id":"W1890161612","doi":"10.1111/j.1865-1682.2010.01166.x","title":"Effective Animal Health Disease Surveillance Using a Network-Enabled Approach","year":2010,"lang":"en","type":"article","venue":"Transboundary and Emerging Diseases","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia; Ministry of Agriculture; Public Health Agency of Canada; Agriculture Food and Rural Development; Canadian Food Inspection Agency","funders":"","keywords":"Disease surveillance; Public health; Business; Government (linguistics); Public health surveillance; Veterinary public health; Population; Animal welfare; Livestock; Biosecurity; Environmental health; Disease; Risk analysis (engineering); Medicine; Geography; Biology","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":[0.000355005,0.000238211,0.0003380663,0.00001598137,0.00091807,0.00009592532,0.0001632746,0.000051295,0.0002168236],"category_scores_gemma":[0.00004662523,0.0001128982,0.0001498052,0.0002574263,0.0002386184,0.0002033195,0.00005653219,0.0001817983,0.000004899952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001231631,"about_ca_system_score_gemma":0.0000289206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003136469,"about_ca_topic_score_gemma":0.0002014008,"domain_scores_codex":[0.9982807,0.0002362848,0.0002407564,0.0005074734,0.0001455326,0.0005892523],"domain_scores_gemma":[0.9991078,0.0001770467,0.00008306537,0.00007742304,0.00002645551,0.0005282102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001926284,0.0005414841,0.9177403,0.0003610332,0.0001453147,0.00003061382,0.0001424383,0.0004733855,0.006351497,0.00823056,0.002890639,0.06116645],"study_design_scores_gemma":[0.0002396192,0.0001576907,0.9792035,0.00002048399,0.00005477972,0.000002361192,0.00007388095,0.006101619,7.898694e-7,0.001313221,0.0125476,0.0002845207],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938019,0.002948668,0.0001260095,0.0018478,0.0001710167,0.0004694094,0.0001747125,0.0001616518,0.0002988375],"genre_scores_gemma":[0.9978199,0.0001696274,0.000184881,0.0008268812,0.0006692953,0.00003991997,0.0002534589,0.000003113087,0.00003293118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06146314,"threshold_uncertainty_score":0.7061145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0160910827638386,"score_gpt":0.2519495883161413,"score_spread":0.2358585055523027,"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."}}