{"id":"W7104027439","doi":"10.5683/sp3/kiu3r6","title":"Transitioning dairy cows to automatic milking: predictive effects of training on post transition AMS use","year":2025,"lang":"","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Milking; Interval training; Automatic milking; Confidence interval; Training (meteorology); Attendance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0005297657,0.0001811616,0.0002033952,0.0001808661,0.0001317125,0.000266828,0.0001731772,0.0003682304,0.00068047],"category_scores_gemma":[0.001756189,0.00009953411,0.0001674036,0.000149405,0.0001619456,0.0001405526,0.0001964689,0.0004200782,0.00007701461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001855158,"about_ca_system_score_gemma":0.0001771575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001757643,"about_ca_topic_score_gemma":0.003855673,"domain_scores_codex":[0.9997498,0.00008207224,0.00001459985,0.00006927752,0.00003479976,0.0000493772],"domain_scores_gemma":[0.998833,0.000505541,0.0003490929,0.0000600683,0.0000537519,0.0001985378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004892725,0.001263304,0.9551687,0.00004004446,0.0001317488,0.00005792804,0.0002970582,0.000560613,0.01586954,0.00002719326,0.0001289757,0.02156215],"study_design_scores_gemma":[0.000004210994,0.0008595381,0.9981864,0.000003883269,0.00001517327,0.0000105552,0.00004703627,0.000489832,0.0003109037,0.0000109425,0.00005975844,0.000001818785],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9998164,0.00003805703,0.00004850039,0.000008113797,0.000001585333,0.000002753994,0.00002286533,0.000001755547,0.00006006525],"genre_scores_gemma":[0.9996204,0.00003468341,0.0001421964,0.000009995768,0.000002617785,0.000009739878,0.00006614853,0.000001254893,0.0001129262],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.001757643,"threshold_uncertainty_score":0.003494799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01681592172020411,"score_gpt":0.265243888213891,"score_spread":0.2484279664936869,"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."}}