{"id":"W3122781137","doi":"10.20944/preprints201901.0126.v1","title":"Mapping Quantitative Trait Loci onto Chromosome-scale Pseudomolecules in Flax","year":2019,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Plant Disease Resistance and Genetics","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Quantitative trait locus; Family-based QTL mapping; Biology; Genetics; Single-nucleotide polymorphism; Chromosome; Population; Inclusive composite interval mapping; SNP; Gene mapping; Computational biology; Gene; Genotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006008304,0.0004494253,0.0004320102,0.001634638,0.0004734769,0.0005158552,0.0004983824,0.0005471248,0.003678434],"category_scores_gemma":[0.001207809,0.0004378577,0.0007576997,0.00164459,0.0003210733,0.0004747328,0.0008333832,0.0007312364,0.001382311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004664021,"about_ca_system_score_gemma":0.0003000757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001644146,"about_ca_topic_score_gemma":0.002751101,"domain_scores_codex":[0.9996647,0.00004873816,0.00002595162,0.000133463,0.00009104775,0.00003613026],"domain_scores_gemma":[0.9992163,0.0003194565,0.0002241869,0.0001143566,0.00005478736,0.000070892],"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":[0.0005924774,0.00007784267,0.003449491,0.0002837954,0.00006254387,0.0003172232,0.0004129207,0.0008509671,0.9676193,0.0009544622,0.0003162656,0.02506286],"study_design_scores_gemma":[0.0003969018,0.0007978278,0.4001893,0.0001827874,0.000282762,0.00192558,0.0004819572,0.01426387,0.5205176,0.003698286,0.05708751,0.0001755148],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8410556,0.001683458,0.1421665,0.0002443712,0.0001026175,0.0004264191,0.009931017,0.001758514,0.00263158],"genre_scores_gemma":[0.7123758,0.001374026,0.2406974,0.0002464339,0.00005178839,0.0006105007,0.03829851,0.00124281,0.0051026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003678434,"threshold_uncertainty_score":0.01230562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09535078128066102,"score_gpt":0.303635870012071,"score_spread":0.20828508873141,"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."}}