{"id":"W2995213394","doi":"10.1186/s12859-019-3207-5","title":"SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution","year":2019,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Université de Sherbrooke","keywords":"Computational biology; Biology; RNA splicing; Alternative splicing; Alignment-free sequence analysis; Intron; Genetics; Gene; Exon; Sequence analysis; Multiple sequence alignment; Sequence (biology); Inference; Sequence alignment; Computer science; RNA; Peptide sequence; Artificial intelligence","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":[0.001655537,0.001550761,0.001394556,0.0008937666,0.0008928381,0.001680842,0.003970148,0.002517844,0.01284147],"category_scores_gemma":[0.004811647,0.001066087,0.002483518,0.0008706561,0.001178895,0.00121948,0.001766808,0.002786935,0.002863374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003228,"about_ca_system_score_gemma":0.001940087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0061829,"about_ca_topic_score_gemma":0.006199467,"domain_scores_codex":[0.9993746,0.000218066,0.00004643411,0.0001417243,0.0001421483,0.00007707784],"domain_scores_gemma":[0.9978077,0.001592631,0.0001007265,0.0001802,0.0001713576,0.0001473775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004895041,0.0001917892,0.0057426,0.0008548195,0.0003881665,0.0005026264,0.0004480858,0.9188661,0.007301729,0.02081086,0.01689017,0.02751357],"study_design_scores_gemma":[0.00007183231,0.00002438384,0.0001710103,0.00002062459,0.00001842443,0.00004682524,0.00001695618,0.9843308,0.001634806,0.007518588,0.006126344,0.00001937349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.07508916,0.0009300387,0.8124172,0.0007439143,0.0005896624,0.0003530291,0.00894933,0.08942021,0.0115075],"genre_scores_gemma":[0.3796538,0.000935549,0.5739291,0.001048008,0.0001829029,0.002248609,0.01613535,0.01953268,0.006334061],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01284147,"threshold_uncertainty_score":0.04295897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04217693886673031,"score_gpt":0.3160184066930021,"score_spread":0.2738414678262718,"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."}}