{"id":"W4410369198","doi":"10.3390/agronomy15051185","title":"QTL Identification and Candidate Gene Prediction for Spike-Related Traits in Barley","year":2025,"lang":"en","type":"article","venue":"Agronomy","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Quantitative trait locus; Spike (software development); Identification (biology); Candidate gene; Biology; Family-based QTL mapping; Gene; Genetics; Computational biology; Gene mapping; Computer science; Botany; Chromosome","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":[0.0001384318,0.00005529339,0.00007628818,0.00001574732,0.00007869449,0.00002699653,0.0000514762,0.00006940644,0.00002589639],"category_scores_gemma":[0.000006897437,0.00002489628,0.00002325284,0.0001194677,0.00002376756,0.00003971446,0.00001466938,0.0000342262,0.00000250517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008630573,"about_ca_system_score_gemma":0.000005616914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001020248,"about_ca_topic_score_gemma":0.0004568799,"domain_scores_codex":[0.9995207,0.00001971838,0.0001514516,0.0001725983,0.00002361553,0.0001118758],"domain_scores_gemma":[0.999876,0.00003599962,0.00002565613,0.00002012709,0.00001937069,0.00002285114],"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":[0.00003283743,0.00005301226,0.04609683,0.00001205881,0.0000138652,9.374309e-7,0.0001264571,0.00001312835,0.7038794,0.002152554,0.001402199,0.2462167],"study_design_scores_gemma":[0.0002565909,0.00007068393,0.9738425,0.00001141186,0.0000121088,0.000001652006,0.00005071787,0.0002081638,0.01227472,0.003751867,0.009453143,0.00006645698],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973237,0.0004606637,0.00007830252,0.001010137,0.0001068027,0.0002467623,0.00003708109,0.0000144783,0.0007221022],"genre_scores_gemma":[0.9986639,0.00008438015,0.00007960289,0.00006508455,0.00004205105,0.00004792591,0.0001386401,3.242513e-7,0.0008780637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9277456,"threshold_uncertainty_score":0.1015241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00951230938748584,"score_gpt":0.2136929125782942,"score_spread":0.2041806031908084,"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."}}