{"id":"W2009302210","doi":"10.1016/j.molcel.2014.08.011","title":"A Global Regulatory Mechanism for Activating an Exon Network Required for Neurogenesis","year":2014,"lang":"en","type":"article","venue":"Molecular Cell","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":146,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Biology; Neurogenesis; Mechanism (biology); Exon; Cell biology; Computational biology; Genetics; Neuroscience; Gene","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":[0.0003755087,0.0001760901,0.0001604292,0.00001963144,0.000177471,0.00004176357,0.0002504174,0.0001584084,0.000001892593],"category_scores_gemma":[0.0001664521,0.000184838,0.0001748097,0.00008242005,0.00002722576,0.00000556944,0.00008352366,0.00003741142,0.000001388409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001639546,"about_ca_system_score_gemma":0.00005965505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001303731,"about_ca_topic_score_gemma":0.00001774181,"domain_scores_codex":[0.9985394,0.00009985649,0.0001824326,0.0004978518,0.000148954,0.0005314936],"domain_scores_gemma":[0.9990877,0.00002173165,0.0000832618,0.0004932827,0.0001393942,0.0001746335],"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":[0.0001703281,0.00003509953,0.00008632452,0.00004503955,0.00002963912,0.000001648886,0.00000397006,0.000652934,0.9899966,0.003036885,0.0006526397,0.005288929],"study_design_scores_gemma":[0.001090365,0.001030045,0.0001124589,0.00001027225,0.00003169967,0.000003989865,0.00001660492,0.01114252,0.9725874,0.003132907,0.01057545,0.0002662833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6791221,0.0001540102,0.31968,0.00006071944,0.00008505943,0.0004527859,0.00001374625,0.00001884841,0.0004126874],"genre_scores_gemma":[0.9790499,0.000008354233,0.01900986,0.0007532023,0.0003830064,0.0001691842,0.0001445846,0.00005191253,0.0004300569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3006701,"threshold_uncertainty_score":0.7537473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01264742074184669,"score_gpt":0.2619345165252916,"score_spread":0.249287095783445,"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."}}