{"id":"W4322749356","doi":"10.1007/978-3-031-16061-5_12","title":"Genomics Assisted Breeding Strategy in Flax","year":2023,"lang":"en","type":"book-chapter","venue":"Compendium of plant genomes","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Genomic selection; Genotyping; Biology; Quantitative trait locus; Selection (genetic algorithm); Genomics; Genome; Computational biology; Genome-wide association study; Plant breeding; Marker-assisted selection; Trait; Genetics; Association mapping; Molecular breeding; Computer science; Genotype; Machine learning; Gene; Single-nucleotide polymorphism; Agronomy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001511593,0.0003581058,0.0004808427,0.0001768456,0.0000398953,0.00001682448,0.0004631467,0.0004739223,0.0001432634],"category_scores_gemma":[0.000009014734,0.0003824459,0.0001569678,0.00003077986,0.0001270872,0.000001698721,0.0002283468,0.0002477072,0.00006916365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003175574,"about_ca_system_score_gemma":0.0002096224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001694854,"about_ca_topic_score_gemma":0.0001436434,"domain_scores_codex":[0.998479,0.00001918852,0.0005157308,0.0005022373,0.0001812776,0.000302572],"domain_scores_gemma":[0.9991289,0.00003830358,0.0002718782,0.0004250408,0.00004756882,0.00008825941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001064773,0.0003250509,0.002840315,0.001567533,0.002253307,0.0001802713,0.0007546807,0.01279165,0.3451092,0.5451329,0.05422884,0.03375145],"study_design_scores_gemma":[0.003452327,0.003215698,0.0890345,0.0008198499,0.0003981542,0.0003011664,0.0004162664,0.0001195731,0.01174459,0.0527978,0.8340598,0.003640249],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04110088,0.009186696,0.0005071111,0.00006909772,0.001711135,0.001146574,0.004203537,0.00007848984,0.9419965],"genre_scores_gemma":[0.2212966,0.003092597,0.005186409,0.00009934804,0.001485121,0.00003026309,0.007425761,0.0003293963,0.7610545],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.779831,"threshold_uncertainty_score":0.9998627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03352448796863704,"score_gpt":0.2355511339317754,"score_spread":0.2020266459631384,"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."}}