{"id":"W3176240244","doi":"10.1016/j.animal.2021.100205","title":"Evaluation of infrared thermography combined with behavioral biometrics for estrus detection in naturally cycling dairy cows","year":2021,"lang":"en","type":"article","venue":"animal","topic":"Effects of Environmental Stressors on Livestock","field":"Agricultural and Biological Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture Food and Rural Development; Alberta Ministry of Agriculture and Forestry; University of Alberta","funders":"Alberta Livestock and Meat Agency; University of Alberta","keywords":"Thermography; Cycling; Biometrics; Estrous cycle; Infrared; Biology; Animal science; Computer science; Artificial intelligence; Optics; Physics","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":[0.000539402,0.0002001508,0.0002704242,0.0005072987,0.0001301535,0.0002841444,0.0001827862,0.0002641696,0.0002731263],"category_scores_gemma":[0.0009100938,0.0001501166,0.0001454412,0.0002428056,0.0001285826,0.0001798199,0.0001779566,0.0001942054,0.00008184569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001511088,"about_ca_system_score_gemma":0.0001364919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008216662,"about_ca_topic_score_gemma":0.002539914,"domain_scores_codex":[0.9996254,0.0001197189,0.00002222785,0.00007417965,0.0001283316,0.00002995472],"domain_scores_gemma":[0.9993749,0.0001430706,0.000289126,0.00002706263,0.0001023275,0.00006347531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001517765,0.0003003058,0.7666982,0.00009873659,0.00008205192,0.00008672388,0.0002087626,0.0002789285,0.2069149,0.0000134102,0.00006025692,0.02374002],"study_design_scores_gemma":[0.000009087384,0.00146516,0.9871365,0.000007151569,0.00005586087,0.0001891022,0.0001174812,0.001566996,0.009325021,0.00001031263,0.0001099972,0.000007383567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991192,0.0001833047,0.0005339368,0.000006028735,0.000002460439,0.000006820164,0.00003458182,0.000004770214,0.0001088099],"genre_scores_gemma":[0.997691,0.0001252389,0.001915339,0.0000161101,0.000009216222,0.00001534663,0.00009266868,0.000002179213,0.0001329915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008216662,"threshold_uncertainty_score":0.002852678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03065536510058115,"score_gpt":0.2691962129168455,"score_spread":0.2385408478162643,"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."}}