{"id":"W4317603924","doi":"10.1101/2023.01.18.524564","title":"Nanovirseq: dsRNA sequencing for plant virus and viroid detection by Nanopore sequencing","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Plant and Fungal Interactions Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université de Sherbrooke; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Centre Sève; Université de Sherbrooke","keywords":"Nanopore sequencing; Biology; Viroid; Illumina dye sequencing; Plant virus; Human virome; Deep sequencing; RNA; DNA sequencing; Metagenomics; Virology; Computational biology; Virus; Genetics; Gene; Genome","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":[0.00159626,0.0008356049,0.0008709489,0.0009573449,0.0005593198,0.0009305567,0.0008053818,0.001025894,0.003302711],"category_scores_gemma":[0.001279974,0.0005729099,0.0008103742,0.0003584122,0.000420486,0.0007645276,0.000850986,0.001214886,0.002289491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004615084,"about_ca_system_score_gemma":0.0005526045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006847979,"about_ca_topic_score_gemma":0.001446083,"domain_scores_codex":[0.9985032,0.0002900343,0.0001252277,0.0006245589,0.0003757224,0.00008127711],"domain_scores_gemma":[0.9992893,0.0002429288,0.0001176185,0.0001257525,0.0001542633,0.00007012983],"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":[0.0002161538,0.00005737205,0.001308167,0.0003562408,0.0000732523,0.00008175876,0.0001205503,0.001045824,0.9674268,0.0006241356,0.002041637,0.02664814],"study_design_scores_gemma":[0.00004977243,0.0003804344,0.005747518,0.0000636033,0.00006392845,0.0003553188,0.00007194684,0.03848608,0.9245643,0.0008601357,0.0292586,0.00009822973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2394969,0.0035418,0.7123289,0.000422619,0.0004710022,0.001160465,0.0146644,0.01951705,0.008396828],"genre_scores_gemma":[0.2072822,0.0007953981,0.7680795,0.0006726736,0.00006691657,0.001326259,0.01457324,0.001338106,0.005865701],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003302711,"threshold_uncertainty_score":0.01104873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02795028719490492,"score_gpt":0.2530736735316257,"score_spread":0.2251233863367208,"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."}}