{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006134366,0.0001184183,0.0001232161,0.00003972447,0.000217887,0.00007931521,0.0003775157,0.00008929292,0.0000173842],"category_scores_gemma":[0.0002379604,0.0001086083,0.00002123721,0.00008406711,0.0001717597,0.000005309405,0.001028307,0.0001248306,0.00002841404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002103366,"about_ca_system_score_gemma":0.00005743479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002070798,"about_ca_topic_score_gemma":0.00005105486,"domain_scores_codex":[0.9987056,0.00006891811,0.0001458709,0.0003854591,0.0002162671,0.0004778781],"domain_scores_gemma":[0.9989304,0.0001063764,0.00003351808,0.0007290842,0.00007811408,0.0001225109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007959596,0.00006841967,0.005126023,0.00002770818,0.0001012744,0.000003041607,0.0003174416,0.0001777039,0.9660928,0.00008502386,0.0006532323,0.02726779],"study_design_scores_gemma":[0.00203213,0.001020761,0.1892452,0.00005634665,0.0000965427,0.00005865923,0.001542405,0.01061473,0.1026963,0.003081731,0.6880507,0.001504448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777547,0.01908319,0.001273126,0.0001756148,0.0001347224,0.0001953435,0.00048533,0.000002486347,0.0008955522],"genre_scores_gemma":[0.9930777,0.002660319,0.002402744,0.00004573347,0.0005720683,0.00001497657,0.0005024253,0.00002034075,0.0007036941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8633965,"threshold_uncertainty_score":0.4428917,"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."}}