{"id":"W1575501363","doi":"10.1038/sj.hdy.6800797","title":"Testing for segregation distortion in genetic scoring data from backcross or doubled haploid populations","year":2006,"lang":"en","type":"article","venue":"Heredity","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Locus (genetics); Biology; Statistics; Genetics; Selection (genetic algorithm); Population; Genetic linkage; Test statistic; Statistic; Mathematics; Statistical hypothesis testing; Computer science; Artificial intelligence; Gene","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":[0.00009989288,0.0001109478,0.0001047436,0.00001921097,0.0001016969,0.00002846362,0.0002037994,0.000108297,0.00001875099],"category_scores_gemma":[0.0001132329,0.0001074255,0.00002291822,0.00008452663,0.0000349382,0.000008630896,0.00009376925,0.00005382671,0.000004183988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001985526,"about_ca_system_score_gemma":0.00006708649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008504713,"about_ca_topic_score_gemma":0.004796347,"domain_scores_codex":[0.9990731,0.00002724124,0.0002483032,0.0003900953,0.00008296926,0.0001782515],"domain_scores_gemma":[0.999348,0.00003476004,0.0000853158,0.0004452395,0.00005314156,0.0000335289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005166281,0.0004217656,0.7507942,0.000097619,0.00003809717,0.000001954424,0.0001047467,0.02090161,0.1984806,0.0006690375,0.006305708,0.02166805],"study_design_scores_gemma":[0.0007832826,0.0001106775,0.9880502,0.00002140189,0.00001960899,0.000002390768,0.00002040803,0.001014939,0.003474625,0.004711336,0.001633147,0.0001579851],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564973,0.0002644748,0.041982,0.00002138948,0.0004197867,0.0002974915,0.0002587018,0.00001750465,0.0002413542],"genre_scores_gemma":[0.8695921,0.000001272183,0.1273497,0.00001701712,0.000837229,0.00003323927,0.001944376,0.00001395941,0.0002110904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.237256,"threshold_uncertainty_score":0.4380687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1144937029688276,"score_gpt":0.3188456525137889,"score_spread":0.2043519495449613,"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."}}