{"id":"W3164371315","doi":"10.1016/j.animal.2021.100233","title":"Using Realistic Evaluation to understand how interventions work on dairy farms","year":2021,"lang":"en","type":"article","venue":"animal","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Alberta Innovates; University of British Columbia; Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Dairy Commission","keywords":"Psychological intervention; Context (archaeology); Intervention (counseling); Colostrum; Animal welfare; Work (physics); Knowledge management; Business; Process management; Applied psychology; Psychology; Operations management; Computer science; Medical education; Nursing; Medicine; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002026087,0.0001231401,0.0001470619,0.00005679295,0.000243565,0.00006888462,0.00006684947,0.00004715252,0.0004022537],"category_scores_gemma":[0.0001526432,0.0001217831,0.0001375389,0.0002469992,0.00003017021,0.00009417743,0.0001193871,0.0001005911,0.00007317703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001751265,"about_ca_system_score_gemma":0.00003592518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003768583,"about_ca_topic_score_gemma":0.00004898562,"domain_scores_codex":[0.9989789,0.0001107181,0.0001465388,0.0002821698,0.0002640776,0.0002176385],"domain_scores_gemma":[0.9995125,0.00004223254,0.00004167965,0.0001836459,0.0001594072,0.0000605205],"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":[0.01265827,0.004056314,0.1469837,0.0008863803,0.001608583,0.00534918,0.02656321,0.0006566748,0.5477368,0.09931113,0.09122018,0.0629696],"study_design_scores_gemma":[0.0006500367,0.002042971,0.9847871,0.0004560497,0.0003967257,0.00007859078,0.009328634,0.0001949783,0.0003334952,0.0005310306,0.0008028256,0.0003975859],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991232,0.0002292657,0.002460684,0.001311942,0.000209864,0.0001906171,0.00003477626,0.00005524753,0.004275602],"genre_scores_gemma":[0.9988495,0.000004622767,0.0005626028,0.0001313312,0.0001172524,0.0000126575,0.00002823589,0.0000193313,0.0002745189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8378034,"threshold_uncertainty_score":0.496617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5275849362312267,"score_gpt":0.4806625130050646,"score_spread":0.04692242322616208,"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."}}