{"id":"W2126457991","doi":"10.1017/s001667230000481x","title":"Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs","year":2000,"lang":"en","type":"article","venue":"Genetics Research","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Iowa State University","keywords":"Quantitative trait locus; Heritability; Statistics; Inclusive composite interval mapping; Binary number; Binary data; Mathematics; Trait; Biology; Genetics; Gene mapping; Computer science; Chromosome","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008412192,0.0001905522,0.0002852371,0.0002829013,0.0001998143,0.00004068082,0.0002602992,0.0002072365,0.00005244088],"category_scores_gemma":[0.00007925709,0.0001812406,0.0001018278,0.0002506931,0.00021301,0.000005746464,0.0001517193,0.0001615982,0.000001990578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001978066,"about_ca_system_score_gemma":0.000127407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009517214,"about_ca_topic_score_gemma":0.00002591621,"domain_scores_codex":[0.9980891,0.0002599317,0.0003673209,0.0004877383,0.0002685527,0.0005273162],"domain_scores_gemma":[0.9993407,0.00006675086,0.00007039836,0.0002008481,0.0001967949,0.0001245034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003069819,0.0001233712,0.001929622,0.00009889322,0.00005411861,0.000008442213,0.001167784,0.0008410233,0.9879899,0.00002070837,0.0002609397,0.007198242],"study_design_scores_gemma":[0.02543949,0.009031196,0.2633353,0.002885525,0.000128422,0.0001652987,0.03189662,0.1658991,0.4378268,0.0012685,0.05874632,0.003377431],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906058,0.004469056,0.003963191,0.00007264756,0.00004350303,0.0004733587,0.00009622756,0.000005728678,0.0002705363],"genre_scores_gemma":[0.961257,0.001249433,0.03665403,0.00004392352,0.00003769081,0.00001451733,0.00004081763,0.00002274217,0.0006797903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5501631,"threshold_uncertainty_score":0.7390779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2331003989467261,"score_gpt":0.398096335609285,"score_spread":0.1649959366625589,"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."}}