{"id":"W4401905691","doi":"10.1101/gad.353718.126","title":"The Competition between Splicing and 3′ Processing Shapes the Human Transcriptome","year":2024,"lang":"en","type":"preprint","venue":"Genes & Development","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hewitt Foundation; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Transcriptome; Competition (biology); RNA splicing; Computational biology; Alternative splicing; Computer science; Biology; Genetics; Gene; Gene expression; Messenger RNA; Ecology; RNA","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002187539,0.000104486,0.0002450286,0.0001224212,0.0001474714,0.0007273025,0.000104882,0.0002141665,0.001100113],"category_scores_gemma":[0.0002726421,0.000171198,0.0001929893,0.0001830197,0.0002541385,0.0002188536,0.000189208,0.0002842411,0.0006058675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002507408,"about_ca_system_score_gemma":0.0002384646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004033844,"about_ca_topic_score_gemma":0.0005438412,"domain_scores_codex":[0.999824,0.0000418605,0.00000660747,0.00006323992,0.00003634934,0.00002802619],"domain_scores_gemma":[0.9999068,0.00003711362,0.00001854226,0.00001142373,0.00001192418,0.00001421644],"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":[0.0004320012,0.00001293219,0.010027,0.00005255714,0.00002436464,0.0002291852,0.00009343679,0.001549794,0.9658834,0.004258146,0.000472645,0.01696455],"study_design_scores_gemma":[0.00006919469,0.000357591,0.2161272,0.00005476916,0.0001627566,0.002495968,0.0006050116,0.0342024,0.6961368,0.02250901,0.02720523,0.00007403541],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816804,0.001898042,0.009891571,0.0003121434,0.00002209592,0.000004434941,0.0003881153,0.0001329131,0.005670338],"genre_scores_gemma":[0.9941781,0.0006084354,0.003177549,0.000137783,0.00001489967,0.000007543255,0.000394605,0.00004108429,0.001439935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001100113,"threshold_uncertainty_score":0.003680289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380347824612304,"score_gpt":0.2973756023507221,"score_spread":0.2735721241045991,"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."}}