{"id":"W2515633145","doi":"10.1111/evj.12638","title":"Use of large‐scale veterinary data for the investigation of antimicrobial prescribing practices in equine medicine","year":2016,"lang":"en","type":"article","venue":"Equine Veterinary Journal","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Animal Welfare Foundation","keywords":"Medical prescription; Medicine; Enrofloxacin; Antimicrobial; Clarithromycin; Population; Family medicine; Antibiotic resistance; Veterinary medicine; Retrospective cohort study; Cohort; Environmental health; Antibiotics; Internal medicine; Ciprofloxacin; Pharmacology; Biology; Microbiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.007120589,0.0003433997,0.0004667642,0.007416677,0.0005854663,0.001651075,0.001048714,0.0006479909,0.003814084],"category_scores_gemma":[0.03956049,0.000272302,0.0004980621,0.009814955,0.0003564019,0.0009315628,0.0009929754,0.0005391483,0.0006851367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002413062,"about_ca_system_score_gemma":0.006320255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1140542,"about_ca_topic_score_gemma":0.1755942,"domain_scores_codex":[0.9932224,0.00148666,0.001364396,0.0008914873,0.002710902,0.0003242673],"domain_scores_gemma":[0.9280745,0.0226175,0.02870309,0.005603055,0.0131169,0.001884977],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002335857,0.0001059313,0.959511,0.001692654,0.0003190111,0.0001791587,0.0008610524,0.0002748432,0.0007521529,0.0003035971,0.006144706,0.02962218],"study_design_scores_gemma":[0.00001377114,0.00009143316,0.9897425,0.000536188,0.0001149162,0.0002005679,0.0005566066,0.0005284925,0.0003134342,0.00007736341,0.00780763,0.00001712862],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7809712,0.006111907,0.003000979,0.001638005,0.000100271,0.001331717,0.1976411,0.000144632,0.009060089],"genre_scores_gemma":[0.9096348,0.002603492,0.006499812,0.0006100915,0.0001020746,0.001068582,0.07839818,0.00003133505,0.001051581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9928794,"threshold_uncertainty_score":0.2267807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1970596394046857,"score_gpt":0.3600194608639785,"score_spread":0.1629598214592927,"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."}}