{"id":"W2359940051","doi":"","title":"Molecular Marker Assisted Selection Technology and Its Application to Crop Breeding","year":2008,"lang":"en","type":"article","venue":"Seed","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Marker-assisted selection; Crop; Biotechnology; Biology; Molecular breeding; Genomic selection; Molecular marker; Evolutionary biology; Agronomy; Genetic marker; Computer science; Genetics; Artificial intelligence; Gene; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004586094,0.00007285934,0.00006770411,0.0000813706,0.0001211018,0.000007569041,0.00006369407,0.0001079995,0.000002953695],"category_scores_gemma":[0.00002738389,0.00007500582,0.00001882406,0.000155336,0.0000210143,0.000001360525,0.00006292071,0.00003791113,0.00001458408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004477357,"about_ca_system_score_gemma":0.0000138565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007873497,"about_ca_topic_score_gemma":0.000002654353,"domain_scores_codex":[0.9995242,0.00001007049,0.00006966878,0.0002151296,0.00005570851,0.0001252022],"domain_scores_gemma":[0.9997857,0.000001598701,0.00002540192,0.00007653576,0.00006204002,0.00004870497],"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":[0.0000240235,0.00001362283,0.01228703,0.000005242594,0.00001519553,0.000002264558,0.00001479467,0.0000298619,0.9863907,0.0001265019,0.0003081168,0.0007827188],"study_design_scores_gemma":[0.0004962736,0.0003590332,0.218477,0.00001228205,0.00002094251,0.0002369872,0.00006716743,0.0006462751,0.7458683,0.00005841526,0.03348727,0.0002700918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945885,0.0001677523,0.003356944,0.0003674065,0.00002857789,0.0001153011,0.000005228174,0.00002418548,0.001346126],"genre_scores_gemma":[0.9983715,0.00004776883,0.0005960773,0.0002208203,0.000039203,0.000008570443,0.00001908715,0.000005759448,0.0006912107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2405224,"threshold_uncertainty_score":0.3058648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009520366833093468,"score_gpt":0.216317245317169,"score_spread":0.2067968784840756,"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."}}