{"id":"W4408240612","doi":"10.5376/mpb.2025.16.0004","title":"Marker-Assisted Selection (MAS) in Soybean Breeding","year":2025,"lang":"en","type":"article","venue":"Molecular Plant Breeding","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Biology; Marker-assisted selection; Selection (genetic algorithm); Biotechnology; Genetic marker; Genomic selection; Microsatellite; Plant breeding; Genetics; Computational biology; Agronomy; Gene; Genotype; Allele; Computer science; Single-nucleotide polymorphism; Artificial intelligence","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":[0.002109215,0.0004755222,0.0007236369,0.0006738623,0.0002997706,0.0006621176,0.0007514692,0.0005988837,0.000654817],"category_scores_gemma":[0.0009882466,0.000326983,0.0004603202,0.001123009,0.0003451267,0.0003830783,0.0006470248,0.0009472431,0.0004644479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004486741,"about_ca_system_score_gemma":0.0004471551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008364557,"about_ca_topic_score_gemma":0.001571186,"domain_scores_codex":[0.99899,0.0003731776,0.00007618403,0.00024358,0.0002709183,0.00004604352],"domain_scores_gemma":[0.9996696,0.000113333,0.0001117982,0.00003881771,0.00004021898,0.00002632717],"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":[0.000406989,0.000144757,0.005318626,0.0009084452,0.0002323582,0.0005955209,0.0002528824,0.006954525,0.5020679,0.01123455,0.001481316,0.4704022],"study_design_scores_gemma":[0.0005013408,0.004607639,0.0656618,0.001055696,0.001257364,0.005366451,0.0004899503,0.09762217,0.4019628,0.02444527,0.3966633,0.0003663065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1849929,0.06472008,0.7334586,0.001299747,0.0005981391,0.0005682565,0.0008701587,0.001914137,0.01157795],"genre_scores_gemma":[0.4474879,0.04634193,0.4977697,0.0005210788,0.0002456768,0.0003765993,0.001117712,0.0001868159,0.005952652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002109215,"threshold_uncertainty_score":0.01115471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01818632750949328,"score_gpt":0.2135650727501759,"score_spread":0.1953787452406826,"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."}}