{"id":"W3037673644","doi":"10.1017/s1751731120001469","title":"Precision livestock farming: real-time estimation of daily protein deposition in growing–finishing pigs","year":2020,"lang":"en","type":"article","venue":"animal","topic":"Effects of Environmental Stressors on Livestock","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Gompertz function; Mathematics; Statistics; Linear regression; Mean squared error; Regression; Quadratic function; Regression analysis; Coefficient of determination; Concordance; Polynomial regression; Animal science; Quadratic equation; Biology","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":[0.001940271,0.0004419454,0.0005549283,0.0003839539,0.000164836,0.0006079829,0.000536521,0.0006928626,0.0004525313],"category_scores_gemma":[0.00222822,0.0003110357,0.0004040111,0.0005527886,0.0001720179,0.0004997675,0.0002298865,0.0002881352,0.0002136369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003537551,"about_ca_system_score_gemma":0.0004064495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008353491,"about_ca_topic_score_gemma":0.008119634,"domain_scores_codex":[0.9996118,0.0001511461,0.00002080462,0.0001196266,0.00007494818,0.00002166402],"domain_scores_gemma":[0.9992694,0.0003971063,0.000142071,0.00008540554,0.00008975794,0.00001626478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002060208,0.0004947479,0.2526088,0.0003384949,0.0005208174,0.0003017491,0.0004180296,0.4677942,0.08537215,0.0007649401,0.001005296,0.1883207],"study_design_scores_gemma":[0.00006717975,0.0005436842,0.159779,0.00002701679,0.0001084888,0.0001742922,0.00007010556,0.8238812,0.01388695,0.0005477812,0.0008517514,0.0000624453],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.887109,0.0002191902,0.1111755,0.00004012639,0.000009135572,0.00003325091,0.0004368471,0.000277827,0.000699021],"genre_scores_gemma":[0.9586473,0.0001144933,0.04010255,0.00001723175,0.000006015184,0.00005862468,0.0006857068,0.00002332262,0.0003447036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008353491,"threshold_uncertainty_score":0.01660973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01419362928547056,"score_gpt":0.2206994989106212,"score_spread":0.2065058696251507,"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."}}