{"id":"W4394966604","doi":"10.5376/cgg.2024.15.0002","title":"The Role of GWAS in Cotton Fiber Quality Improvement","year":2024,"lang":"en","type":"article","venue":"Cotton Genomics and Genetics","topic":"Dyeing and Modifying Textile Fibers","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fiber; Genome-wide association study; Quality (philosophy); Quality management; Business; Materials science; Biology; Composite material; Physics; Genetics; Marketing; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01832471,0.0007298597,0.0009919807,0.001815047,0.0007477814,0.001969127,0.0006851883,0.001004518,0.0024873],"category_scores_gemma":[0.03145542,0.0003262796,0.001628785,0.002690722,0.001277555,0.001407499,0.00116665,0.00149827,0.0002933407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007557865,"about_ca_system_score_gemma":0.001014892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002710463,"about_ca_topic_score_gemma":0.003727638,"domain_scores_codex":[0.9853798,0.009551938,0.0008155485,0.002362256,0.001564313,0.0003261783],"domain_scores_gemma":[0.9708362,0.0219094,0.002449414,0.002526163,0.001738973,0.0005398584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001102899,0.0001623812,0.5055827,0.001251499,0.004482534,0.001377591,0.001090409,0.003261558,0.01494104,0.01925135,0.006705247,0.4407909],"study_design_scores_gemma":[0.0002039896,0.001108868,0.8238325,0.001098401,0.005655242,0.002626869,0.0008964659,0.01608184,0.007558238,0.06020548,0.08050531,0.0002268182],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.486898,0.1357995,0.3063934,0.0449019,0.003220256,0.0003180924,0.003361719,0.001695584,0.01741163],"genre_scores_gemma":[0.8926053,0.01866012,0.07628825,0.007399111,0.001179479,0.0001410108,0.0009017599,0.0002833211,0.002541604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01832471,"threshold_uncertainty_score":0.09691155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00801620496840963,"score_gpt":0.2298547354149477,"score_spread":0.2218385304465381,"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."}}