{"id":"W4394475330","doi":"10.6084/m9.figshare.19795435","title":"Construction of an evenly-distributed genetic map using contig-tag-SNPs for quantitative trait loci (QTL) analysis of fiber-related traits in kenaf (<i>Hibiscus cannabinus</i> L.)","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Hibiscus Plant Research Studies","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"Kenaf; Quantitative trait locus; Hibiscus; Contig; Biology; Trait; Genetic analysis; Fiber; Genetics; Botany; Composite material; Computer science; Gene; Genome; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003151616,0.0005252346,0.000553822,0.001815501,0.000550998,0.0003427269,0.0005163028,0.000280215,0.001617578],"category_scores_gemma":[0.0002665406,0.0003649381,0.0006925777,0.00138785,0.0002576969,0.0002570601,0.0005692686,0.0005716079,0.000496073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004458444,"about_ca_system_score_gemma":0.0007667238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008955128,"about_ca_topic_score_gemma":0.01404977,"domain_scores_codex":[0.9997577,0.00002149737,0.00001591564,0.0001287613,0.00004435991,0.00003176536],"domain_scores_gemma":[0.9998707,0.00002568081,0.00003321543,0.00001528253,0.00002063442,0.00003454096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006625546,0.0002792897,0.008326898,0.0002899059,0.0000847083,0.0007264002,0.0004784324,0.001710146,0.9345771,0.001351432,0.0003924354,0.05112068],"study_design_scores_gemma":[0.001046961,0.001631937,0.5523264,0.0002114505,0.00129321,0.003507655,0.001368406,0.03182415,0.3493434,0.003062495,0.05411784,0.0002660968],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.888801,0.0008435961,0.1002463,0.0001829697,0.00003555707,0.0004117738,0.00510201,0.0008261871,0.003550475],"genre_scores_gemma":[0.7394243,0.001069139,0.2275843,0.000111884,0.00002006241,0.000613174,0.02273166,0.0001898199,0.008255712],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.008955128,"threshold_uncertainty_score":0.01780599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1497361969483827,"score_gpt":0.444338250712467,"score_spread":0.2946020537640843,"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."}}