{"id":"W7134288098","doi":"10.26181/14714742","title":"Multiple country approach to improve the test-day prediction of dairy cows’ dry matter intake","year":2021,"lang":"","type":"article","venue":"La Trobe University","topic":"Effects of Environmental Stressors on Livestock","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dry matter; Mean squared error; Regression; Artificial neural network; Partial least squares regression; Regression analysis; Linear regression; Dairy cattle","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002624914,0.0002454307,0.0002783372,0.00001666283,0.0004300403,0.00005117998,0.0005417452,0.0002357765,0.0005302384],"category_scores_gemma":[0.0001441789,0.000124262,0.0002101521,0.0004323409,0.000427323,0.0002402952,0.0005996966,0.0003310853,0.00007395671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001565496,"about_ca_system_score_gemma":0.00001782566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008335588,"about_ca_topic_score_gemma":0.0002441807,"domain_scores_codex":[0.9980938,0.0004427943,0.0002099223,0.0005844236,0.0003284459,0.0003405686],"domain_scores_gemma":[0.9982302,0.001143391,0.0001666089,0.0002282544,0.0000518714,0.0001797368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001669745,0.00166654,0.7522534,0.00008064181,0.0001380276,0.00002809753,0.0007405827,0.0003512175,0.2349009,0.0003300529,0.004727685,0.004615957],"study_design_scores_gemma":[0.0005436851,0.0003924292,0.9655071,0.00005103268,0.000122536,0.000005664594,0.00330821,0.0004394023,0.003896697,0.00002869589,0.02549265,0.0002119206],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803026,0.0001244906,0.0001390088,0.001081115,0.0002615096,0.0006049722,0.001496992,0.00002883043,0.01596043],"genre_scores_gemma":[0.9930324,0.0000809882,0.0005092682,0.0003119525,0.0001531565,0.000002218562,0.000097737,0.000003076332,0.005809198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2310042,"threshold_uncertainty_score":0.5805739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007016431917204213,"score_gpt":0.1624606057714527,"score_spread":0.1554441738542484,"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."}}