{"id":"W1157926539","doi":"","title":"Genotype-environment interaction between Chile and North America and between Chilean herd environmental categories for milk yield traits in Black and White cattle","year":2015,"lang":"en","type":"article","venue":"Animal Science Papers and Reports","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sire; Herd; Bivariate analysis; White (mutation); Genetic correlation; Biology; Animal science; Trait; Gene–environment interaction; Selection (genetic algorithm); Beef cattle; Statistics; Geography; Genotype; Genetic variation; Mathematics; Genetics","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":[0.0007798501,0.0002209139,0.0002859195,0.000704863,0.0002964168,0.0006073062,0.0001982685,0.0002188649,0.001681638],"category_scores_gemma":[0.001198808,0.0001697971,0.0004241168,0.0006144652,0.0004911857,0.0001457004,0.000503178,0.000246078,0.00009579225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00053144,"about_ca_system_score_gemma":0.0005337969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01914673,"about_ca_topic_score_gemma":0.03712212,"domain_scores_codex":[0.9993265,0.0003317313,0.00002926735,0.0001714025,0.00005530374,0.0000858672],"domain_scores_gemma":[0.9987877,0.0006555957,0.0002294749,0.000087162,0.00007495627,0.0001651469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001011533,0.00008256271,0.967003,0.00003736514,0.0005238667,0.0003644561,0.001178795,0.0005336603,0.02607815,0.0002303461,0.0001225121,0.002833701],"study_design_scores_gemma":[0.000005578099,0.00002650477,0.9992309,0.000003647474,0.00002285176,0.00003162313,0.0002537441,0.000170949,0.0001541171,0.00002358424,0.00007257885,0.000004036454],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997445,0.0000260641,0.00003510085,0.000007420967,5.62984e-7,0.000001098514,0.0000423711,0.000001605459,0.0001412635],"genre_scores_gemma":[0.9995492,0.00002602759,0.00008520456,0.0000107561,0.000001078363,0.000006147103,0.0001277546,0.000003367448,0.0001903964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01914673,"threshold_uncertainty_score":0.03807056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530028032228648,"score_gpt":0.2260223946796936,"score_spread":0.2107221143574071,"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."}}