{"id":"W2110727901","doi":"10.1080/10888700902719914","title":"Research and Teaching of Dairy Cattle Well Being: Finding Synergy Between Ethology and Epidemiology","year":2009,"lang":"en","type":"article","venue":"Journal of Applied Animal Welfare Science","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Ethology; Animal welfare; Epidemiology; Context (archaeology); Welfare; Curriculum; Animal health; Psychology; Medical education; Medicine; Veterinary medicine; Political science; Pedagogy; Biology; Ecology; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007931154,0.0001326939,0.0005019336,0.0001475397,0.0006440639,0.00003055777,0.0005028098,0.0001169746,0.0000332562],"category_scores_gemma":[0.0007038106,0.00005892558,0.00005576281,0.0003534292,0.00114044,0.000201034,0.0002608257,0.000491614,0.000002321636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003620693,"about_ca_system_score_gemma":0.00002050022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004871836,"about_ca_topic_score_gemma":0.000005982612,"domain_scores_codex":[0.9979821,0.000230069,0.0005926523,0.0003670464,0.0002897622,0.000538306],"domain_scores_gemma":[0.9980226,0.001142283,0.0003891167,0.00005793442,0.0001395365,0.0002484918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004292178,0.00009396305,0.139987,0.00002572955,0.00002489269,0.0000166838,0.0003581508,0.0000198235,0.1981701,0.5978997,0.0005502527,0.06242452],"study_design_scores_gemma":[0.0001268824,0.001684335,0.9712703,0.00002186987,0.00001591201,0.00002239335,0.001136742,0.00004219522,0.0003498517,0.02255151,0.002672541,0.0001054478],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792427,0.0001715642,0.00001588034,0.009584034,0.00003514211,0.00008403442,0.000002541854,0.00001055031,0.01085348],"genre_scores_gemma":[0.9984677,0.00008939845,0.0009005934,0.0002953197,0.0002216108,9.412023e-7,0.000001767788,9.247325e-7,0.00002176346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8312833,"threshold_uncertainty_score":0.4953684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07598500943070455,"score_gpt":0.3526766673811882,"score_spread":0.2766916579504837,"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."}}