{"id":"W4252675765","doi":"10.21203/rs.2.12872/v1","title":"Nanopore native RNA sequencing of a human poly(A) transcriptome: RNA extraction, cDNA conversion and direct RNA and cDNA library preparation for Oxford Nanopore","year":2019,"lang":"en","type":"preprint","venue":"Research Square","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Michael Smith Health Research BC; University of British Columbia; University of Toronto; Ontario Institute for Cancer Research","funders":"Biotechnology and Biological Sciences Research Council; Canadian Institutes of Health Research; Medical Research Council; Surgical Reconstruction and Microbiology Research Centre; Government of Ontario; National Institutes of Health; Ontario Institute for Cancer Research; Oxford Nanopore Technologies; Wellcome Trust","keywords":"RNA; Nanopore sequencing; Complementary DNA; cDNA library; Computational biology; Nanopore; Transcriptome; Biology; RNA extraction; DNA sequencing; Molecular biology; Genetics; Gene; Gene expression; Nanotechnology","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":[0.0006665028,0.0006651325,0.0007896853,0.0005613833,0.0009341189,0.000750092,0.0005661508,0.0006997472,0.005372209],"category_scores_gemma":[0.0007326461,0.0006071835,0.0005982073,0.0007164478,0.0003557545,0.000428304,0.0005414676,0.001340636,0.003942537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004812769,"about_ca_system_score_gemma":0.0007805069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001281802,"about_ca_topic_score_gemma":0.005130055,"domain_scores_codex":[0.999408,0.00007008788,0.0000426464,0.0001946953,0.000194252,0.00009039676],"domain_scores_gemma":[0.9996428,0.0001124515,0.00001778615,0.0001184202,0.00007043783,0.00003811438],"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":[0.0001442683,0.00002410128,0.0001928236,0.0001599056,0.00002318656,0.00006868239,0.00008655821,0.0004382996,0.9838658,0.0009790242,0.002861683,0.01115566],"study_design_scores_gemma":[0.00001831601,0.00007962738,0.002451105,0.00001937547,0.00002229642,0.0002437256,0.000031819,0.004066528,0.9598625,0.001481192,0.03170289,0.00002064063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1777096,0.00265955,0.7331671,0.0009027061,0.0005488374,0.0006477569,0.05309994,0.01070843,0.0205561],"genre_scores_gemma":[0.2316149,0.002343242,0.6386642,0.001023424,0.0001791458,0.001763957,0.08523001,0.003368492,0.03581258],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005372209,"threshold_uncertainty_score":0.01797181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04430105701986949,"score_gpt":0.3726044508670562,"score_spread":0.3283033938471868,"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."}}