{"id":"W2027305723","doi":"10.1007/s11032-015-0224-6","title":"Single-nucleotide polymorphism identification and genotyping in Camelina sativa","year":2015,"lang":"en","type":"article","venue":"Molecular Breeding","topic":"Lipid metabolism and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Plant Biotechnology Institute; Saskatchewan Research Council (Canada); Agriculture and Agri-Food Canada","funders":"Saskatchewan Canola Development Commission","keywords":"Biology; Camelina sativa; Genetics; Single-nucleotide polymorphism; SNP genotyping; Molecular Inversion Probe; Genotyping; Oryza sativa; SNP array; SNP; dbSNP; Population; Molecular breeding; Genomics; Computational biology; Genome; Genotype; Gene; Crop; Agronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000367508,0.000139334,0.0001355099,0.0001006268,0.00004707738,0.00005323482,0.0001280101,0.0001132797,0.000001984892],"category_scores_gemma":[0.0002008234,0.0001441809,0.00003769607,0.0001223752,0.00005433461,0.000009993781,0.0001294745,0.00006686525,0.000008697471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002219279,"about_ca_system_score_gemma":0.00004135176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004782152,"about_ca_topic_score_gemma":0.00002169536,"domain_scores_codex":[0.9989853,0.00005678666,0.000233187,0.0003482702,0.0001462632,0.0002302155],"domain_scores_gemma":[0.9995226,0.000006648167,0.000076649,0.0002209993,0.00005737382,0.0001157565],"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":[0.00002190167,0.00002718491,0.002327111,0.000009129903,0.0000128343,0.000007492436,0.0001638939,0.000007465003,0.9834342,0.00007162517,0.00009031626,0.01382685],"study_design_scores_gemma":[0.0004238791,0.00004893808,0.005412039,0.00002331174,0.00001609171,0.0000183481,0.0002030051,0.0000792116,0.9818523,0.00008291783,0.01163079,0.0002091841],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942493,0.002264323,0.002247184,0.0002236806,0.0002160093,0.000116222,0.000002753894,0.0000156606,0.0006648348],"genre_scores_gemma":[0.9980621,0.00003087957,0.001281115,0.0001850782,0.0002700733,0.000008315801,0.00002489281,0.00002563645,0.0001119397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01361766,"threshold_uncertainty_score":0.5879527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02096024009024398,"score_gpt":0.2336800106934367,"score_spread":0.2127197706031928,"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."}}