{"id":"W3121733167","doi":"10.1371/journal.pone.0245742","title":"Anticipatory behaviour as an indicator of the welfare of dairy calves in different housing environments","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"AgResearch","keywords":"Anticipation (artificial intelligence); Psychology; Quality (philosophy); Welfare; Reward system; Developmental psychology; Neuroscience; Computer science","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":[0.0006197772,0.0003269179,0.0004685411,0.000472351,0.0002494967,0.0006525273,0.0003307251,0.0004280607,0.0008669172],"category_scores_gemma":[0.001145066,0.000207567,0.0003268135,0.0002445038,0.0003820503,0.0003366131,0.0004894002,0.0007296893,0.00009742781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005271012,"about_ca_system_score_gemma":0.0003194094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002966383,"about_ca_topic_score_gemma":0.006195418,"domain_scores_codex":[0.9992883,0.0001193658,0.0000502672,0.0001662534,0.0002103015,0.0001656528],"domain_scores_gemma":[0.9987636,0.0002341461,0.0004891593,0.00006100488,0.0001444889,0.0003076915],"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":[0.002922281,0.0005926908,0.2681676,0.0002181827,0.0001765609,0.0001907486,0.0009825072,0.000477645,0.7156854,0.00007903373,0.00008927221,0.01041826],"study_design_scores_gemma":[0.00000898847,0.001654394,0.9829775,0.000011955,0.00006035509,0.00006801226,0.0002708639,0.0004845097,0.01425174,0.00003679397,0.0001585222,0.00001629774],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993762,0.0001213345,0.0003137958,0.000006805797,0.000002352702,0.000007101131,0.00005601075,0.000003183986,0.0001131444],"genre_scores_gemma":[0.9981964,0.0001559658,0.0008898107,0.00002957517,0.000005742672,0.00003410986,0.0002138124,0.000004922716,0.0004696113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002966383,"threshold_uncertainty_score":0.005898237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09743816686686399,"score_gpt":0.3079683942939757,"score_spread":0.2105302274271117,"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."}}