{"id":"W2102813686","doi":"10.1101/gr.142232.112","title":"iReckon: Simultaneous isoform discovery and abundance estimation from RNA-seq data","year":2012,"lang":"en","type":"article","venue":"Genome Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Hospital for Sick Children; BC Cancer Agency; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Biology; Computational biology; RNA-Seq; Gene isoform; Alternative splicing; RNA splicing; Intron; Transcriptome; splice; RNA; Gene; Genetics; Gene expression","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":[0.007199334,0.00195421,0.001511656,0.001731549,0.0007270128,0.002112718,0.002206414,0.001287323,0.001499636],"category_scores_gemma":[0.009955167,0.001145293,0.001453536,0.001301411,0.000764911,0.001621537,0.001835373,0.002516766,0.001158476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008182118,"about_ca_system_score_gemma":0.001267299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654936,"about_ca_topic_score_gemma":0.004189865,"domain_scores_codex":[0.9972693,0.0006650271,0.0001495957,0.001050597,0.0007494292,0.0001159893],"domain_scores_gemma":[0.9950524,0.003073409,0.0006251749,0.0006275144,0.0004946546,0.0001268693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001403746,0.000418989,0.03615059,0.001700385,0.001839078,0.0007982347,0.0008105935,0.1548333,0.3525303,0.01210127,0.01767836,0.4197351],"study_design_scores_gemma":[0.00007436358,0.0001120257,0.005310389,0.00005000415,0.00009919272,0.0003987339,0.00006988697,0.9054766,0.07453611,0.007691285,0.006037218,0.0001442214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02459857,0.0002957766,0.9614776,0.0001165781,0.00007814773,0.000135985,0.002051051,0.01067894,0.0005673774],"genre_scores_gemma":[0.07080734,0.0002992735,0.9201494,0.0001795582,0.0000470832,0.0004332438,0.004874797,0.002123574,0.001085818],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007199334,"threshold_uncertainty_score":0.03807414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07963213856054606,"score_gpt":0.3577748787679911,"score_spread":0.278142740207445,"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."}}