{"id":"W2145654768","doi":"10.1017/s1014233900001590","title":"Genetic base and inbreeding of Canadienne, Brown Swiss, Holstein and Jersey cattle in Canada","year":2003,"lang":"en","type":"article","venue":"Animal Genetic Resources Information","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Agriculture and Agri-Food Canada","funders":"","keywords":"Inbreeding; Pedigree chart; Brown Swiss; Breed; Biology; Population; Animal science; Dairy cattle; Effective population size; Artificial insemination; Beef cattle; Herd; Demography; Biotechnology; Genetic diversity; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006047843,0.0001499822,0.0002609874,0.001484545,0.001905228,0.0007509245,0.0005657387,0.0001759142,0.001272551],"category_scores_gemma":[0.0007831343,0.0001374985,0.0001755466,0.00180658,0.0007342128,0.000139747,0.0003491457,0.0003525544,0.0001198792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01000842,"about_ca_system_score_gemma":0.005925121,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9814689,"about_ca_topic_score_gemma":0.9930646,"domain_scores_codex":[0.9995747,0.00003872839,0.00001236937,0.00009221386,0.0001575405,0.0001243685],"domain_scores_gemma":[0.9991809,0.00009597239,0.00007311696,0.00002675039,0.0004057034,0.0002175518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003486334,0.00004900961,0.9749488,0.00003176865,0.0001402861,0.0003209833,0.00357388,0.0004262045,0.004645736,0.0006701587,0.0007791846,0.01406545],"study_design_scores_gemma":[0.000007978981,0.00002756638,0.9972221,0.000009680492,0.00002235299,0.00006349957,0.001140759,0.0002895854,0.0001482092,0.00004335691,0.001018061,0.000006932106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979751,0.0002041184,0.00007356893,0.0000414688,0.000002276019,0.000007554069,0.0003766576,0.000003637214,0.001315733],"genre_scores_gemma":[0.9979461,0.0001842649,0.000179546,0.000023951,0.000001584716,0.000003941284,0.0006642686,0.000003337907,0.0009930688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01853108,"threshold_uncertainty_score":0.07261652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005418572918065665,"score_gpt":0.1745527193488653,"score_spread":0.1691341464307997,"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."}}