{"id":"W4400618598","doi":"10.1101/2024.07.11.603067","title":"Accurate isoform quantification by joint short- and long-read RNA-sequencing","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Genome Canada","funders":"National Cancer Institute; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada","keywords":"Computational biology; Gene isoform; Joint (building); RNA; Computer science; Biology; Genetics; Gene; Engineering","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":[0.002527588,0.0007002792,0.0006651084,0.000429601,0.0003162451,0.0009448846,0.0009152326,0.0008584257,0.0007121792],"category_scores_gemma":[0.003092056,0.0005214175,0.0006858269,0.0006007402,0.0006994248,0.001193242,0.0008151259,0.001160607,0.0006747096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006517395,"about_ca_system_score_gemma":0.0006659955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001083349,"about_ca_topic_score_gemma":0.00155054,"domain_scores_codex":[0.999083,0.0001928168,0.00004560579,0.0003239944,0.00030887,0.00004574832],"domain_scores_gemma":[0.9987404,0.000594329,0.0001919,0.0002780097,0.0001576727,0.00003775154],"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":[0.0002379012,0.0001093241,0.008347079,0.0003162312,0.0001608761,0.0001845651,0.0001927779,0.2412328,0.6573071,0.0195611,0.001559072,0.07079136],"study_design_scores_gemma":[0.000009555331,0.00005526624,0.0021723,0.00001504313,0.00002449381,0.00008273438,0.00001986531,0.8432983,0.1397857,0.01188069,0.002624047,0.00003199956],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05723787,0.0003328183,0.939209,0.0001172324,0.00006468084,0.00004534411,0.0003584951,0.001451641,0.00118297],"genre_scores_gemma":[0.4324,0.0006911581,0.5631515,0.0001722519,0.00005954511,0.0001755449,0.0009237029,0.0006461949,0.001780069],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002527588,"threshold_uncertainty_score":0.01336735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02476843116717174,"score_gpt":0.2642529076987956,"score_spread":0.2394844765316238,"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."}}