{"id":"W4240133244","doi":"10.1136/vr.j57","title":"Equine disease surveillance: quarterly summary","year":2017,"lang":"en","type":"article","venue":"Veterinary Record","topic":"Helminth infection and control","field":"Veterinary","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Disease surveillance; Animal health; Veterinary medicine; Disease; Medicine; Environmental health; Geography; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.003732009,0.0009046816,0.0005747394,0.006770415,0.000248657,0.001709457,0.0006587175,0.0005939988,0.0139471],"category_scores_gemma":[0.0132548,0.0004084027,0.0005180965,0.005758201,0.0001532292,0.001080517,0.0006728763,0.0007128304,0.009448898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007693974,"about_ca_system_score_gemma":0.002083865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01596568,"about_ca_topic_score_gemma":0.01594179,"domain_scores_codex":[0.9963977,0.0004621761,0.001123577,0.0003192701,0.001466002,0.0002312213],"domain_scores_gemma":[0.9812464,0.001430958,0.003386869,0.0006413973,0.01246327,0.0008310644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001947735,0.00008818701,0.04584766,0.002263921,0.0001123146,0.00009466374,0.0001404653,0.0004397303,0.0006470376,0.0001918577,0.7824884,0.167491],"study_design_scores_gemma":[0.00004718597,0.0003606422,0.4224129,0.001335327,0.00009221022,0.0005349898,0.0003648808,0.0005382536,0.0007559445,0.0001459456,0.5733747,0.00003700855],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04661359,0.03950673,0.006430731,0.01593998,0.006638064,0.001553945,0.8087053,0.003220188,0.07139154],"genre_scores_gemma":[0.1112437,0.05190469,0.007963467,0.004056495,0.005524493,0.001281122,0.7642903,0.0005751363,0.05316066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01596568,"threshold_uncertainty_score":0.04665768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08014560675635725,"score_gpt":0.3553601190024905,"score_spread":0.2752145122461332,"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."}}