{"id":"W2155201678","doi":"10.1093/bioinformatics/btt092","title":"EBARDenovo: highly accurate <i>de novo</i> assembly of RNA-Seq with efficient chimera-detection","year":2013,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"De Bruijn graph; Sequence assembly; De Bruijn sequence; Computer science; Computational biology; De novo transcriptome assembly; Amplicon; RNA-Seq; Software; RNA; Chimera (genetics); Biology; Graph; Genetics; Gene; Transcriptome; Theoretical computer science; Mathematics; Programming language; Gene expression; Combinatorics; Polymerase chain reaction","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001089136,0.0001568039,0.0001585976,0.00003908101,0.00007665656,0.00003046196,0.0001492208,0.00009092838,0.000006458084],"category_scores_gemma":[0.00002411851,0.0001222059,0.0000599208,0.00008813078,0.00007254727,0.000002001145,0.00008631963,0.00005519325,0.00002621081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000136407,"about_ca_system_score_gemma":0.00006280403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004091135,"about_ca_topic_score_gemma":0.0000144495,"domain_scores_codex":[0.9991952,0.00001395082,0.0002991826,0.000119089,0.0001278693,0.0002446923],"domain_scores_gemma":[0.9993027,0.00001055208,0.000182161,0.0002774265,0.0001585808,0.00006857855],"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":[0.00004481894,0.0000581738,0.0003831601,0.0000758538,0.0001219788,4.117161e-7,0.0003634833,0.003413058,0.9904772,0.00004066588,0.0004698149,0.004551363],"study_design_scores_gemma":[0.0008825673,0.0008061447,0.008170051,0.00002439717,0.0000489356,0.00003647242,0.000494908,0.008267589,0.9739159,0.0000229123,0.006989887,0.0003401724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988909,0.0002027746,0.006558338,0.00006133584,0.0001123939,0.0002658286,0.00001997381,0.000006766706,0.0038636],"genre_scores_gemma":[0.993927,0.0001248393,0.00551057,0.0001441513,0.00007417036,0.00002622914,0.00001439092,0.00001551346,0.0001631304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01656125,"threshold_uncertainty_score":0.4983413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007075047158963154,"score_gpt":0.2059673794860584,"score_spread":0.1988923323270953,"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."}}