{"id":"W4206576889","doi":"10.3389/fvets.2021.757776","title":"The Prevalence of Integument Injuries and Associated Risk Factors Among Canadian Turkeys","year":2022,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Ontario Genomics; Ontario Genomics Institute; Genome Canada","keywords":"Flock; Logistic regression; Veterinary medicine; Feather pecking; Rump; Demography; Pecking order; Medicine; Environmental health; Biology; Animal science; Ecology; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004310454,0.0004135553,0.0002823752,0.001386768,0.001568359,0.0008225784,0.0007810471,0.0004153681,0.0020009],"category_scores_gemma":[0.001611275,0.0004025721,0.0004874046,0.002122834,0.0006968739,0.0003284167,0.0005217924,0.0004526357,0.0002017707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01319234,"about_ca_system_score_gemma":0.00608672,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9846435,"about_ca_topic_score_gemma":0.992753,"domain_scores_codex":[0.9995191,0.00002397416,0.00002727947,0.0001043753,0.0001907834,0.0001345013],"domain_scores_gemma":[0.9989952,0.00006317911,0.0003058222,0.00003916555,0.0003924145,0.0002042289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002632279,0.00001391234,0.9972507,0.00001377081,0.00001962104,0.0000641677,0.0003085265,0.00005860364,0.0001781321,0.00002271418,0.0002589942,0.001784417],"study_design_scores_gemma":[0.000001156813,0.00001313654,0.9991536,0.000009092039,0.000007570437,0.00005201857,0.0004442503,0.00009864258,0.00001760037,0.000004711102,0.0001946039,0.000003528015],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978441,0.0002393338,0.00004785338,0.00007785103,0.000003419915,0.00001125936,0.0009362757,0.000005586781,0.0008343538],"genre_scores_gemma":[0.9981152,0.0003274123,0.0001657047,0.00003497244,0.000002329985,0.000006492396,0.0008689966,0.000002975743,0.0004759869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01535654,"threshold_uncertainty_score":0.09571761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0124839688348726,"score_gpt":0.2107371658353638,"score_spread":0.1982531970004912,"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."}}