{"id":"W3186158899","doi":"10.1016/j.prevetmed.2021.105444","title":"Development and evaluation of a new method to combine clinical impression survey data with existing laboratory data for veterinary syndromic surveillance with the Canada West Swine Health Intelligence Network (CWSHIN)","year":2021,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Manitoba; University of Saskatchewan; Shared Health; University of Prince Edward Island","funders":"","keywords":"Identifier; Merge (version control); Population; Data collection; Unique identifier; Medicine; Data science; Computer science; Veterinary medicine; Environmental health; Statistics; Information retrieval","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":[0.0396625,0.001695868,0.001307915,0.007930945,0.00118559,0.004049121,0.002945136,0.001286726,0.002719953],"category_scores_gemma":[0.07021339,0.001513655,0.00282307,0.006674702,0.0008649279,0.004008958,0.004314456,0.002113804,0.001339328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002681497,"about_ca_system_score_gemma":0.006272689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03471935,"about_ca_topic_score_gemma":0.03641908,"domain_scores_codex":[0.973736,0.01103465,0.002880101,0.0048797,0.006740569,0.0007290103],"domain_scores_gemma":[0.9454093,0.02859623,0.003865201,0.004392089,0.01683895,0.0008982101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008024023,0.0009553949,0.1664099,0.0008558186,0.001916044,0.0002938574,0.003712639,0.03526405,0.01162859,0.008300909,0.0102926,0.7595679],"study_design_scores_gemma":[0.000259059,0.0005858793,0.04640184,0.0002276169,0.0005199407,0.0004011901,0.002127885,0.9042293,0.0127592,0.007345988,0.02491298,0.0002290799],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02918537,0.00015869,0.9609137,0.000441034,0.0001347057,0.001783621,0.001780794,0.004229867,0.001372284],"genre_scores_gemma":[0.04540445,0.00005001566,0.95089,0.00007742987,0.0000284932,0.0009537052,0.001863318,0.0002109973,0.0005215649],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9652807,"threshold_uncertainty_score":0.2097578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4551592329607337,"score_gpt":0.4720178813392836,"score_spread":0.01685864837854989,"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."}}