{"id":"W6913050624","doi":"10.5683/sp3/vbjtwq","title":"ODRC data schema: Tie stalls and maternity milkings","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Schema (genetic algorithms); Raw data; Documentation; Data collection; Data quality; Conceptual schema; Sample (material)","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":[0.001413226,0.001548378,0.001169912,0.003165443,0.0009987397,0.002513952,0.003307183,0.001767141,0.06047242],"category_scores_gemma":[0.004727294,0.0009497766,0.00134411,0.007454107,0.0005129581,0.001996344,0.00213195,0.001543865,0.06353633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003820228,"about_ca_system_score_gemma":0.005103582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1690936,"about_ca_topic_score_gemma":0.2653984,"domain_scores_codex":[0.9985029,0.0001607988,0.0002142841,0.0004377354,0.000465924,0.0002184831],"domain_scores_gemma":[0.9973672,0.0003889276,0.0002213925,0.0006368929,0.001118093,0.0002675102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005159793,0.00002127317,0.001449666,0.0004612608,0.000021608,0.00002297481,0.00007458634,0.0002702429,0.0002268434,0.001011192,0.9939097,0.002479096],"study_design_scores_gemma":[0.00005277171,0.000006092123,0.004145541,0.0001569384,0.00001483937,0.00004614389,0.0001634887,0.0002183669,0.0003107813,0.0004744483,0.9943897,0.00002083706],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001233617,0.00002604759,0.000128091,0.00004912272,0.00001573594,0.00001442953,0.998353,0.0002785079,0.001011737],"genre_scores_gemma":[0.0003934178,0.00003461639,0.0004303587,0.00003682285,0.000002347366,0.00004728003,0.9983903,0.00008351779,0.0005814182],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1690936,"threshold_uncertainty_score":0.3362187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0481747010222116,"score_gpt":0.3128590044546695,"score_spread":0.2646843034324579,"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."}}