{"id":"W2994807934","doi":"10.1101/2019.12.11.869693","title":"Chromosome-scale genome assembly provides insights into rye biology, evolution, and agronomic potential","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; Agriculture and Agri-Food Canada; National Research Council Canada; University of Saskatchewan","funders":"Agriculture and Agri-Food Canada; Directorate for Biological Sciences; German Network for Bioinformatics Infrastructure; Bundesministerium für Bildung und Forschung; European Regional Development Fund; Deutsche Forschungsgemeinschaft; Bundesministerium für Ernährung und Landwirtschaft; Biotechnology and Biological Sciences Research Council; Grantová Agentura České Republiky; Leibniz-Gemeinschaft; Universitätsmedizin Göttingen","keywords":"Triticeae; Secale; Biology; Triticale; Genome; Genetics; Chromosome; Plant disease resistance; Chromosome engineering; Genome evolution; Gene; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003265948,0.0005998565,0.0005723636,0.001134311,0.0003765232,0.001136205,0.0003080534,0.0004812617,0.003792298],"category_scores_gemma":[0.0008136523,0.0004470128,0.0007345406,0.0007516977,0.0002171008,0.0006405019,0.0006385996,0.001088456,0.00258294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002720841,"about_ca_system_score_gemma":0.0003759649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002641137,"about_ca_topic_score_gemma":0.004771437,"domain_scores_codex":[0.9998374,0.00001693364,0.000008950979,0.00007596371,0.00003979319,0.00002089992],"domain_scores_gemma":[0.9996495,0.00009883385,0.00003554034,0.0001019348,0.00006874245,0.0000453809],"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":[0.0003437865,0.0000614427,0.00950495,0.0002967685,0.0001671376,0.0003762442,0.0002592226,0.003421528,0.9562477,0.0015591,0.002901138,0.02486104],"study_design_scores_gemma":[0.000187311,0.0003418699,0.3561778,0.0002011811,0.0005049176,0.001418211,0.000639401,0.08150972,0.4053007,0.01047447,0.1430694,0.0001749895],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6398454,0.003066149,0.2630107,0.0008006428,0.0001910546,0.0001405388,0.0758373,0.008125491,0.008982752],"genre_scores_gemma":[0.5797813,0.00190076,0.2257175,0.0001730285,0.00006089048,0.000141393,0.1843794,0.002291913,0.005553922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003792298,"threshold_uncertainty_score":0.01268643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00916079534378547,"score_gpt":0.1924479513059205,"score_spread":0.183287155962135,"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."}}