{"id":"W1978794870","doi":"10.1186/1471-2164-12-77","title":"Model SNP development for complex genomes based on hexaploid oat using high-throughput 454 sequencing technology","year":2011,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Agriculture and Agri-Food Canada","funders":"Agricultural Research Service; National Institute of Food and Agriculture; General Mills; U.S. Department of Agriculture","keywords":"Biology; Genetics; Molecular Inversion Probe; SNP genotyping; Tag SNP; Genome; Amplicon; Genotyping; Computational biology; Single-nucleotide polymorphism; Contig; Genomics; SNP; Genotype; Gene; Polymerase chain reaction","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":[0.0001634412,0.0001866705,0.0002248464,0.00003553542,0.0003115241,0.0000242329,0.0002693909,0.0001776563,0.00006514973],"category_scores_gemma":[0.000009635683,0.00008870877,0.00007498463,0.0001323632,0.00007032951,0.00002470813,0.00007637057,0.00007710613,0.00001623256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001125523,"about_ca_system_score_gemma":0.0000924706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004825019,"about_ca_topic_score_gemma":0.0004421297,"domain_scores_codex":[0.998885,0.00002203696,0.0002568293,0.0003666227,0.00007929048,0.0003902052],"domain_scores_gemma":[0.9996266,0.00004835215,0.00008897547,0.00009668086,0.00007224574,0.00006714308],"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":[0.0000718143,0.0000759631,0.002291138,0.00001508326,0.00001004703,0.000002287394,0.0002310793,0.00592883,0.977068,0.001107334,0.00004694671,0.01315146],"study_design_scores_gemma":[0.001436426,0.001642679,0.0144815,0.00004856394,0.00008876262,0.0000319429,0.001080387,0.4599859,0.4777402,0.02285982,0.01894214,0.001661643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885101,0.00009057917,0.01039584,0.0001113584,0.0001182313,0.0003218109,0.00005284984,0.00006011548,0.0003391388],"genre_scores_gemma":[0.7955189,0.00001255072,0.2038884,0.0003195881,0.0001057958,0.00002357439,0.00006872052,0.000003165916,0.00005931011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4993278,"threshold_uncertainty_score":0.3617439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2154368584488957,"score_gpt":0.2609631402078247,"score_spread":0.04552628175892903,"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."}}