{"id":"W106150465","doi":"10.2202/1544-6115.1410","title":"Testing for Gene-Gene Interaction with AMMI Models","year":2010,"lang":"en","type":"article","venue":"Statistical Applications in Genetics and Molecular Biology","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"","keywords":"Ammi; Gene interaction; Biplot; Main effect; Interaction; Gene–environment interaction; Computational biology; Additive genetic effects; Biology; Multiplicative function; Genetics; Gene; Trait; Mixed model; Computer science; Mathematics; Genotype; Statistics; Heritability","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":[0.00009891474,0.0001371847,0.0001285192,0.0000485823,0.0001002775,0.00002323379,0.0001158036,0.0001401882,0.000003782912],"category_scores_gemma":[0.00004702825,0.0001210939,0.00002159129,0.00006904734,0.0001515737,0.000001610093,0.00007127778,0.00009895101,0.000001005323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003273674,"about_ca_system_score_gemma":0.0000408598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002676538,"about_ca_topic_score_gemma":0.00005096587,"domain_scores_codex":[0.9991418,0.00002019492,0.0001654498,0.0004042856,0.00004455623,0.0002237852],"domain_scores_gemma":[0.9994967,0.00005640357,0.00005154974,0.0002063083,0.0001011976,0.00008786409],"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":[0.00004072387,0.00005805066,0.004455686,0.00001360408,0.00002186532,0.000001236686,0.00001417649,0.0002202406,0.9630667,0.02439679,0.00004603231,0.0076649],"study_design_scores_gemma":[0.004052316,0.00392353,0.02329264,0.00003053075,0.0002335155,0.0002458009,0.0003902172,0.01845119,0.7160097,0.1364121,0.09513681,0.001821685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4586307,0.000151613,0.5401613,0.00004931619,0.00003440953,0.0003086899,0.0002412369,0.000006679952,0.0004159993],"genre_scores_gemma":[0.7922938,0.00003704741,0.2068433,0.0001223786,0.00005630581,0.0001252506,0.000491378,0.00001161987,0.00001882575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3336631,"threshold_uncertainty_score":0.4938067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635226709220338,"score_gpt":0.285890504062962,"score_spread":0.2695382369707586,"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."}}