{"id":"W3048288596","doi":"","title":"New Twists in Detecting mRNA Modification Dynamics","year":2020,"lang":"en","type":"article","venue":"PMC","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Nucleotide; Computational biology; Biology; Messenger RNA; Identification (biology); Gene; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.007069945,0.000711631,0.001005107,0.001873667,0.0006318514,0.002767423,0.001297582,0.001751418,0.002702424],"category_scores_gemma":[0.007774009,0.0007139984,0.0006635187,0.0009966413,0.00370573,0.005839922,0.001856749,0.005115044,0.0008899308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008225521,"about_ca_system_score_gemma":0.0006453983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006143546,"about_ca_topic_score_gemma":0.001551294,"domain_scores_codex":[0.9976962,0.0007671621,0.0001131635,0.0005456103,0.0007517945,0.0001260861],"domain_scores_gemma":[0.9922101,0.005191473,0.0003559742,0.0009309432,0.0008413083,0.000470103],"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":[0.0006227625,0.0001252313,0.01167176,0.00228902,0.0003936847,0.0004292936,0.001646529,0.003456324,0.6766812,0.07729132,0.01067543,0.2147175],"study_design_scores_gemma":[0.00009383562,0.00105812,0.02435495,0.000955561,0.0003076658,0.003380384,0.002238834,0.03358363,0.3946254,0.2666925,0.2721119,0.0005971353],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1354911,0.1532809,0.6310857,0.04340526,0.004281977,0.0001195852,0.001772356,0.003081551,0.02748152],"genre_scores_gemma":[0.4797624,0.07202146,0.4143378,0.01605148,0.003995365,0.0003255936,0.001219957,0.0009975856,0.01128828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007069945,"threshold_uncertainty_score":0.03738987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02190375271853124,"score_gpt":0.2676095862025699,"score_spread":0.2457058334840386,"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."}}