{"id":"W6969164452","doi":"10.5683/sp3/3dztlt","title":"ODRC data schema: Voluntary milking system (VMS) data","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Fisheries and Aquaculture Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Milking; Schema (genetic algorithms); Automatic milking; Raw data; Data collection; Documentation","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":[0.001749864,0.001099654,0.0008075063,0.002599912,0.0008905423,0.002250372,0.002386542,0.001607931,0.04138608],"category_scores_gemma":[0.006187152,0.0006968885,0.001018077,0.006154911,0.0004418055,0.001811574,0.001854527,0.00145236,0.04223567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003422034,"about_ca_system_score_gemma":0.004993048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1156302,"about_ca_topic_score_gemma":0.1493715,"domain_scores_codex":[0.9984659,0.0001820259,0.0002670015,0.0003914557,0.0004940857,0.0001996057],"domain_scores_gemma":[0.996341,0.0005629973,0.0002971128,0.0008817428,0.001634688,0.0002823279],"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":[0.00006882343,0.00002613494,0.00205751,0.0005516607,0.00002027916,0.00002874761,0.00009028724,0.0004427611,0.0004045281,0.001803063,0.9911181,0.003388162],"study_design_scores_gemma":[0.00004685881,0.000006485108,0.003678974,0.0001581106,0.00001150624,0.00003725876,0.0001620863,0.0003141277,0.0005018724,0.00058613,0.9944773,0.00001930104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001972373,0.00002470853,0.0002394087,0.00006513352,0.00001722305,0.00002936232,0.9976789,0.0004266901,0.001321306],"genre_scores_gemma":[0.0005975098,0.00003392569,0.0007355456,0.00004658911,0.000002786682,0.0000805343,0.9977597,0.0001298625,0.0006135235],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1156302,"threshold_uncertainty_score":0.2299144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06581126165216271,"score_gpt":0.2658670230662556,"score_spread":0.2000557614140929,"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."}}