{"id":"W2274989230","doi":"10.1111/avj.12411","title":"Demographics of Australian horses: results from an internet‐based survey","year":2016,"lang":"en","type":"article","venue":"Australian Veterinary Journal","topic":"Veterinary Equine Medical Research","field":"Veterinary","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demographics; Horse racing; Horse; Veterinary medicine; Geography; Quarter (Canadian coin); Demography; Medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003543827,0.0006217519,0.000804278,0.0006536812,0.000187149,0.0001760365,0.00189475,0.0004608012,0.004194617],"category_scores_gemma":[0.001546422,0.0004517567,0.0004322802,0.0006261157,0.0008526942,0.001058448,0.0003510306,0.001106038,0.000271663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002152629,"about_ca_system_score_gemma":0.0003227804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001246404,"about_ca_topic_score_gemma":0.00006246565,"domain_scores_codex":[0.9921507,0.002275962,0.001855424,0.0009306819,0.001463793,0.001323462],"domain_scores_gemma":[0.9947877,0.001194593,0.000759125,0.001344309,0.0005014723,0.001412796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.05823958,0.002527878,0.09260529,0.000198315,0.0009531999,0.02949855,0.001089986,0.00001773662,0.6869273,0.00007109445,0.06972643,0.05814467],"study_design_scores_gemma":[0.0127559,0.06463499,0.8270783,0.002184557,0.0001384911,0.009807389,0.0004584633,0.000217446,0.01000172,0.0007374725,0.07017189,0.001813389],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929112,0.00002080755,0.0005843774,0.003324058,0.0009336435,0.0002929429,0.001595611,0.0001124905,0.000224836],"genre_scores_gemma":[0.9933991,0.00004846258,0.002628524,0.0001056805,0.0005386189,0.00001429065,0.0001858274,0.0001117847,0.002967718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.734473,"threshold_uncertainty_score":0.9997934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.263006677695868,"score_gpt":0.4328665326141099,"score_spread":0.1698598549182419,"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."}}