{"id":"W4323321677","doi":"10.1016/j.animal.2023.100763","title":"Review: Fundamentals, limitations and pitfalls on the development and application of precision nutrition techniques for precision livestock farming","year":2023,"lang":"en","type":"review","venue":"animal","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Livestock; Computer science; Temptation; Precision agriculture; Process (computing); Control (management); Risk analysis (engineering); Agriculture; Data science; Artificial intelligence; Business; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002894206,0.0009813093,0.002578013,0.003790613,0.0006047958,0.002801512,0.002004277,0.002577228,0.005571666],"category_scores_gemma":[0.00830333,0.0005943474,0.001575416,0.00517395,0.001270126,0.003708645,0.001446915,0.003096801,0.003153206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001513167,"about_ca_system_score_gemma":0.004766305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002396056,"about_ca_topic_score_gemma":0.003512967,"domain_scores_codex":[0.9984157,0.0003501413,0.0003513668,0.0002216726,0.0005599731,0.000101103],"domain_scores_gemma":[0.991619,0.00530081,0.000864406,0.0002307844,0.00172002,0.0002649585],"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":[0.00009346465,0.00004802745,0.0002562697,0.1311926,0.0003218652,0.0002536424,0.0002491126,0.0005980029,0.001616475,0.01473534,0.1519145,0.6987208],"study_design_scores_gemma":[0.000008487314,0.00005806418,0.0003576093,0.01606924,0.0001799965,0.0003364653,0.00008096586,0.00006161837,0.000248576,0.002465192,0.9801077,0.0000260921],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009749964,0.9947276,0.0003413242,0.002318346,0.001135152,0.00001523745,0.00007388281,0.00001904171,0.001272069],"genre_scores_gemma":[0.0006323606,0.9963195,0.0003547036,0.001519629,0.0006263858,0.00002105328,0.00007213958,0.000005727262,0.0004484529],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005571666,"threshold_uncertainty_score":0.01863909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1285619649741449,"score_gpt":0.330577624333639,"score_spread":0.202015659359494,"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."}}