{"id":"W2101019506","doi":"10.1186/1471-2164-8-424","title":"High throughput SNP discovery and genotyping in grapevine (Vitis vinifera L.) by combining a re-sequencing approach and SNPlex technology","year":2007,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":275,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto Madrileño de Investigación y Desarrollo Rural, Agrario y Alimentario; Genome Canada","keywords":"Biology; Genetics; SNP genotyping; Genotyping; Single-nucleotide polymorphism; Molecular Inversion Probe; DNA sequencing; Genotype; Genetic diversity; SNP; Reference genome; Coding region; Genome; Whole genome sequencing; Computational biology; Gene; Population","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001271946,0.0004747751,0.0008691628,0.0006020545,0.0002871948,0.0007928496,0.0005051914,0.0006026826,0.000835072],"category_scores_gemma":[0.001238846,0.0004611555,0.0005305583,0.0003898372,0.0002438763,0.0002685927,0.0004880648,0.0007096224,0.0008652218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002979548,"about_ca_system_score_gemma":0.0003455031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008293932,"about_ca_topic_score_gemma":0.001934553,"domain_scores_codex":[0.998908,0.0001807333,0.00007629033,0.0005552183,0.0002202382,0.00005941848],"domain_scores_gemma":[0.9992282,0.0003058127,0.0001065795,0.0001441392,0.0001459698,0.00006927254],"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":[0.0001653664,0.0001181028,0.008012109,0.0002488134,0.0001364903,0.0001746966,0.0002268793,0.001646447,0.9553923,0.0001927761,0.0004084173,0.0332776],"study_design_scores_gemma":[0.000109524,0.002115598,0.1739814,0.00008897213,0.0006630048,0.002280026,0.0002192233,0.03194501,0.7589035,0.0008065493,0.02876716,0.0001200114],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8594202,0.002381278,0.1306136,0.0001501506,0.00007763183,0.0004749345,0.003626889,0.001126812,0.002128478],"genre_scores_gemma":[0.6015963,0.001459682,0.3700686,0.0003381806,0.00005107394,0.0005529525,0.01859386,0.0002774195,0.0070619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001271946,"threshold_uncertainty_score":0.006726801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04708502102174326,"score_gpt":0.2619574883532993,"score_spread":0.214872467331556,"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."}}