{"id":"W3024979179","doi":"","title":"A longitudinal study describing horse demographics and movements during a competition season in Ontario, Canada.","year":2018,"lang":"en","type":"article","venue":"PubMed","topic":"Veterinary Equine Medical Research","field":"Veterinary","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Geography; Humanities; Demographics; Population; Demography; Cartography; Art; Sociology","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":[0.0007358046,0.0002395724,0.0002379307,0.001193326,0.00239523,0.00088029,0.0006172659,0.0003064075,0.001088605],"category_scores_gemma":[0.001878343,0.0003082831,0.0002878381,0.002594016,0.0004004278,0.0005444826,0.0004830541,0.0004230804,0.0002216375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01326674,"about_ca_system_score_gemma":0.01801547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9812747,"about_ca_topic_score_gemma":0.9930906,"domain_scores_codex":[0.9993665,0.0000540435,0.00003907339,0.00008840175,0.0002419199,0.0002100897],"domain_scores_gemma":[0.9979918,0.00008506238,0.0005295163,0.00006155653,0.0009507427,0.0003813148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002374149,0.0000228988,0.9955614,0.00001608437,0.00001359859,0.00009188463,0.001231098,0.00002202902,0.0001805972,0.0000215312,0.0006950651,0.002120089],"study_design_scores_gemma":[0.000001185165,0.00002008735,0.9979819,0.00001245969,0.000005327838,0.00003373886,0.001273602,0.00004285014,0.00001007892,0.000004861388,0.0006117006,0.000002263821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924434,0.0004923152,0.0002274424,0.0002418359,0.00001011837,0.0001142575,0.004679296,0.00000896593,0.001782327],"genre_scores_gemma":[0.993431,0.0006254877,0.0004741414,0.0001820534,0.000007532894,0.00009408852,0.003530106,0.000005241444,0.001650242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01872534,"threshold_uncertainty_score":0.09625739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1508886883690245,"score_gpt":0.3131330823657645,"score_spread":0.16224439399674,"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."}}