{"id":"W4312176562","doi":"10.3168/jds.2022-22370","title":"Phenotypic analysis of heat stress in Holsteins using test-day production records and NASA POWER meteorological data","year":2022,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Effects of Environmental Stressors on Livestock","field":"Agricultural and Biological Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Agriculture and Agri-Food Canada; Canada First Research Excellence Fund; Canadian Dairy Commission; Dairy Farmers of Canada","keywords":"Heat stress; Production (economics); Environmental science; Statistics; Animal science; Mathematics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0006493274,0.0002384251,0.0002445446,0.0008337505,0.0004654233,0.0005733867,0.000394045,0.0001576715,0.0006544253],"category_scores_gemma":[0.001233386,0.0001211,0.0002893123,0.001212438,0.0002774717,0.0001481088,0.0002076133,0.0002211042,0.0001039816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003847936,"about_ca_system_score_gemma":0.002123943,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8356724,"about_ca_topic_score_gemma":0.9302063,"domain_scores_codex":[0.9996586,0.00005375018,0.00001438516,0.00008532024,0.0001041185,0.00008371917],"domain_scores_gemma":[0.9992065,0.0001974231,0.0001474824,0.0000511675,0.0002704583,0.0001269923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001733129,0.00002589137,0.9856529,0.00001506986,0.0001117568,0.00005259201,0.0004001915,0.0008301283,0.00517613,0.00004978447,0.0001713619,0.007340886],"study_design_scores_gemma":[6.046023e-7,0.0000146752,0.9991928,0.000001276685,0.000006142028,0.000007761652,0.00008279458,0.0005242709,0.00009154523,0.000002877794,0.00007374641,0.00000160865],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985719,0.00004384233,0.0003067141,0.000006284254,7.734251e-7,0.000006285932,0.0007807757,0.000006950266,0.0002764712],"genre_scores_gemma":[0.9975913,0.00004209709,0.0006505445,0.000007868062,9.484546e-7,0.00000784539,0.001232539,0.000004975114,0.0004618986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8356724,"threshold_uncertainty_score":0.3305906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03211160201480828,"score_gpt":0.2628010117306558,"score_spread":0.2306894097158476,"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."}}