{"id":"W2626055486","doi":"","title":"The Relationship Between 30-, 60-, 90- and 120-Day Non-Returns to Service in the Artificial Insemination of Dairy Cattle in Ontario","year":2016,"lang":"en","type":"article","venue":"Canadian journal of agricultural science/Canadian Journal of Agricultural Science","topic":"Reproductive Physiology in Livestock","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial insemination; Fertility; Insemination; Animal science; Dairy cattle; Service (business); Biology; Agricultural science; Business; Demography; Pregnancy; Marketing; Botany; Sperm; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004455317,0.00009201968,0.0001503115,0.000328248,0.0006667683,0.0004402677,0.0004045274,0.0001915155,0.001638164],"category_scores_gemma":[0.001467587,0.0001055726,0.000245077,0.0005786328,0.0003687703,0.0001441802,0.0002874024,0.0003457753,0.0001597642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008024404,"about_ca_system_score_gemma":0.005275553,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9202278,"about_ca_topic_score_gemma":0.9807737,"domain_scores_codex":[0.999703,0.00003380215,0.0000157404,0.0000407589,0.0001170019,0.00008964817],"domain_scores_gemma":[0.9982067,0.0003089722,0.0004414685,0.00003444167,0.0004900995,0.0005182286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004711618,0.00002895711,0.9912199,0.0000315668,0.00004271554,0.00008106581,0.001870786,0.0001465534,0.001126755,0.0001081944,0.0006182469,0.004254049],"study_design_scores_gemma":[0.000002041243,0.00001792781,0.9991172,0.000002489755,0.000003606227,0.0000113173,0.000365629,0.00004664613,0.00003403227,0.000005026787,0.0003922805,0.000001698601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970353,0.0002070342,0.00005814134,0.0001297327,0.000005394265,0.000007171064,0.001135977,0.000002799272,0.001418525],"genre_scores_gemma":[0.995878,0.0001958087,0.0000697494,0.0000264699,0.000004266988,0.000006822107,0.001155269,0.000002023282,0.002661505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07977217,"threshold_uncertainty_score":0.1604839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03695951425158069,"score_gpt":0.2358655888414451,"score_spread":0.1989060745898644,"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."}}