{"id":"W2564125431","doi":"10.1101/057455","title":"A Common Class of Transcripts with 5′-Intron Depletion, Distinct Early Coding Sequence Features, and N <sup>1</sup> -Methyladenosine Modification","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Canada Research Chairs; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Institutes of Health; Krembil Foundation; Canada Excellence Research Chairs, Government of Canada; Canadian Institutes of Health Research; Avon Foundation for Women","keywords":"Intron; Biology; Genetics; Coding region; Exon; Untranslated region; Gene; RefSeq; RNA; Start codon; Stop codon; Computational biology; Messenger RNA; Genome","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":[0.0001833045,0.0002149052,0.0001609555,0.0005376762,0.0002097417,0.0002074528,0.0001685301,0.0002491351,0.001408325],"category_scores_gemma":[0.0004811509,0.00007904896,0.000259856,0.0003871222,0.00023331,0.0000998207,0.0001912164,0.0002187266,0.0003797517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244095,"about_ca_system_score_gemma":0.0001255371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003611376,"about_ca_topic_score_gemma":0.0007124735,"domain_scores_codex":[0.9998275,0.00001435194,0.00002014193,0.00006452871,0.00003633969,0.00003710742],"domain_scores_gemma":[0.9993247,0.0002006947,0.0002266686,0.00007850381,0.00007392417,0.00009543481],"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":[0.0004288686,0.00002947769,0.08003463,0.0001275964,0.00003303757,0.00138729,0.0001488252,0.0002415348,0.9030253,0.0003013872,0.0003780831,0.01386405],"study_design_scores_gemma":[0.00003432602,0.0005561112,0.6445712,0.00005313183,0.0001416035,0.01139229,0.0002990832,0.006898492,0.3232218,0.001295391,0.01150357,0.00003305606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917191,0.0004336316,0.005232277,0.00003768659,0.00001487982,0.00001868135,0.001592588,0.0001290833,0.0008220004],"genre_scores_gemma":[0.9932743,0.0001203074,0.002791931,0.00006803982,0.00002494046,0.00003195794,0.002758321,0.000030164,0.0008999894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001408325,"threshold_uncertainty_score":0.00471139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0149767312996883,"score_gpt":0.2237628033476773,"score_spread":0.208786072047989,"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."}}