{"id":"W3083213233","doi":"10.1016/j.psj.2020.08.054","title":"Multiphasic nonlinear mixed growth models for laying hens","year":2020,"lang":"en","type":"article","venue":"Poultry Science","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Wageningen University and Research; University of Alberta; Egg Farmers of Canada; Alberta Agriculture and Forestry","keywords":"Gompertz function; Weight gain; Logistic regression; Mathematics; Animal science; Inflection point; Body weight; Statistics; Biology; Medicine; Internal medicine","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":[0.006051008,0.002416071,0.001493384,0.001835191,0.0006525356,0.001322406,0.002451621,0.001807703,0.003933765],"category_scores_gemma":[0.008302882,0.00138335,0.002664983,0.0007951818,0.0007534957,0.000894414,0.001441884,0.002409909,0.001405108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001558745,"about_ca_system_score_gemma":0.001248685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02616347,"about_ca_topic_score_gemma":0.01990771,"domain_scores_codex":[0.9977813,0.001441022,0.00008531968,0.0003643623,0.0001513289,0.0001767169],"domain_scores_gemma":[0.9945397,0.004186962,0.0005073262,0.0001638193,0.0005039045,0.00009831927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002897099,0.00006615902,0.003458169,0.00007796835,0.0002367926,0.0001050726,0.0001187405,0.9799216,0.0007732165,0.003824689,0.0003528809,0.01077505],"study_design_scores_gemma":[0.00001058217,0.00004711239,0.0004051243,0.000007350525,0.00001660281,0.000007518196,0.00001379806,0.9981012,0.00007691543,0.001053134,0.0002492816,0.0000114798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1442723,0.001437716,0.8487185,0.0004929789,0.0001425098,0.0004063594,0.001391351,0.001244024,0.001894308],"genre_scores_gemma":[0.8405867,0.0008687697,0.1378976,0.0002572928,0.0001189987,0.001895506,0.002625666,0.0003213527,0.01542808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02616347,"threshold_uncertainty_score":0.05202234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07358863163990041,"score_gpt":0.2497526472227108,"score_spread":0.1761640155828104,"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."}}