{"id":"W4321509859","doi":"10.21423/aabppro20163493","title":"Estrus detection intensity and accuracy and optimal timing of insemination with automated activity monitors for dairy cows","year":2016,"lang":"en","type":"article","venue":"American Association of Bovine Practitioners Conference Proceedings","topic":"Reproductive Physiology in Livestock","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Insemination; Artificial insemination; Herd; Estrous cycle; Dairy industry; Dairy cattle; Computer science; Animal science; Biology; Pregnancy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002688149,0.0001049105,0.0002347709,0.00003093853,0.0001048097,0.00002118956,0.00005097728,0.00005522907,0.000004714906],"category_scores_gemma":[0.001448378,0.00004845123,0.00002271298,0.0001851161,0.000258654,0.0007166761,0.00003423398,0.00006674033,2.694811e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007738799,"about_ca_system_score_gemma":0.00001785075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002352606,"about_ca_topic_score_gemma":0.00001222808,"domain_scores_codex":[0.9992594,0.00002604799,0.0001696651,0.0002729536,0.0001468251,0.0001250863],"domain_scores_gemma":[0.9974141,0.0004599039,0.001164748,0.00002424611,0.0008978304,0.00003923741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003234051,0.00004448755,0.04237031,0.00001372164,0.00003811873,2.520688e-8,0.0001971314,4.516203e-7,0.9072943,0.00006564757,0.00003684511,0.04961561],"study_design_scores_gemma":[0.0002546081,0.002053219,0.8299723,0.00004788769,0.00004011815,0.000003744496,0.001243188,0.0008477637,0.1652139,0.0001597196,0.00004437583,0.0001192041],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968912,0.000002921988,0.0003161806,0.002343395,0.00002459042,0.0002815053,0.00002855404,0.00006303777,0.00004863553],"genre_scores_gemma":[0.998553,0.00004961947,0.001267759,0.00001444481,0.00004283042,0.00003854425,0.000006794263,0.000001545877,0.00002548311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7876019,"threshold_uncertainty_score":0.1975784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01651477190673476,"score_gpt":0.2554401424165192,"score_spread":0.2389253705097844,"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."}}