{"id":"W3106949473","doi":"10.1093/jas/skaa054.212","title":"238 Linking livestock phenomics and precision livestock farming","year":2020,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Effects of Environmental Stressors on Livestock","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Phenomics; Livestock; Agriculture; Animal welfare; Biotechnology; Productivity; Agricultural science; Quality (philosophy); Production (economics); Business; Biology; Genomics; Ecology","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":[0.005085316,0.0004759319,0.0005786088,0.002023594,0.0004271073,0.002945392,0.0008561491,0.0007666905,0.003998468],"category_scores_gemma":[0.006413139,0.0002588,0.0004555011,0.002669084,0.001006254,0.001254118,0.001948428,0.0008428347,0.001022265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001371712,"about_ca_system_score_gemma":0.001516554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002612808,"about_ca_topic_score_gemma":0.002456372,"domain_scores_codex":[0.997045,0.00114714,0.0001454476,0.0006525647,0.0008653702,0.0001444887],"domain_scores_gemma":[0.9898071,0.003779282,0.00249372,0.001008181,0.002383045,0.0005287099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000585779,0.0003269016,0.3169886,0.001701744,0.0005631362,0.000924265,0.0009127058,0.013105,0.04307962,0.0139248,0.01375931,0.5941281],"study_design_scores_gemma":[0.00008793452,0.001191739,0.672051,0.001542224,0.0004616694,0.001800449,0.002568716,0.03531114,0.03485959,0.09771176,0.1521626,0.0002511157],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5335085,0.03039478,0.3324396,0.02202275,0.001753766,0.0004799634,0.01109436,0.002410006,0.0658964],"genre_scores_gemma":[0.8347017,0.01086089,0.1394286,0.002993881,0.001004497,0.0002741881,0.004521436,0.0002447883,0.005970101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005085316,"threshold_uncertainty_score":0.02689403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380335105140901,"score_gpt":0.2357619630975444,"score_spread":0.2119586120461353,"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."}}