{"id":"W2024544257","doi":"10.2135/cropsci2003.2018","title":"Genetic Components of Yield Stability in Maize Breeding Populations","year":2003,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diallel cross; Biology; Agronomy; Selection (genetic algorithm); Trait; Population; Stability (learning theory); Grain yield; Additive genetic effects; Plant breeding; Genetic gain; Genetic variability; Genetic variation; Biotechnology; Genetics; Genotype; Heritability; Gene; Hybrid","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":[0.0004618241,0.00005336176,0.00008081048,0.00001977079,0.0001499225,0.00003601563,0.0002292136,0.00002524663,0.0001713373],"category_scores_gemma":[0.0001816904,0.00002327474,0.00002160891,0.0006663524,0.0001712069,0.00006631391,0.00003957215,0.00004897322,0.000004255563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001640498,"about_ca_system_score_gemma":0.00001144934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000560042,"about_ca_topic_score_gemma":0.0005894567,"domain_scores_codex":[0.999195,0.00001588862,0.0001694651,0.0001972714,0.0002136391,0.0002087552],"domain_scores_gemma":[0.999726,0.00006656177,0.00004888724,0.00004449373,0.00005158281,0.00006247991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[8.138862e-7,0.00001676736,0.3426721,0.000001317666,1.386287e-7,3.506491e-7,0.00002870949,0.00003496543,0.6557593,0.0003410986,0.000003465021,0.001140971],"study_design_scores_gemma":[0.00002886116,0.00003936631,0.9775618,0.00001367052,0.000001019329,0.000003252133,0.000101994,0.0003112693,0.02095445,0.0007613105,0.0001618406,0.00006121218],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977074,0.00004059521,0.000007905604,0.00007343527,0.0001382612,0.0000754335,0.000009565293,0.00000645005,0.001940966],"genre_scores_gemma":[0.9992881,0.000005396816,0.0006599869,0.00001848087,0.00001380632,0.000001365296,0.000001297098,2.10024e-7,0.00001136358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6348897,"threshold_uncertainty_score":0.1876024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1455561451209413,"score_gpt":0.2498147712523067,"score_spread":0.1042586261313654,"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."}}