{"id":"W4391261909","doi":"10.1093/bioinformatics/btae051","title":"TKSM: highly modular, user-customizable, and scalable transcriptomic sequencing long-read simulator","year":2024,"lang":"en","type":"article","venue":"Bioinformatics","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Michael Smith Health Research BC","keywords":"Computer science; Modular design; Scalability; Software; Human–computer interaction; Operating system; Computer architecture","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":[0.0001540034,0.0001660633,0.0001355284,0.00007032222,0.0001031368,0.0001645223,0.0001356477,0.0001509684,0.0000344291],"category_scores_gemma":[0.00001585054,0.0001466029,0.00007038318,0.0001340537,0.0000717279,0.00003037117,0.00004287917,0.00009342317,0.0000519948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004906815,"about_ca_system_score_gemma":0.0001621338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001947789,"about_ca_topic_score_gemma":0.00001550492,"domain_scores_codex":[0.999126,0.0000131959,0.0002926054,0.0001994683,0.0001232474,0.0002455343],"domain_scores_gemma":[0.9994687,0.000009356933,0.00004225496,0.0003241852,0.00005360123,0.0001018742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002214748,0.0001594442,0.002657749,0.00326426,0.0008914705,0.00004045571,0.002647909,0.02844811,0.7866852,0.01079333,0.05677242,0.1074182],"study_design_scores_gemma":[0.001195365,0.0002730874,0.0009664287,0.0002346788,0.0001605835,0.0001121099,0.0004993361,0.4931671,0.08475839,0.0002347342,0.4175212,0.0008769476],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9342629,0.005734244,0.05556343,0.0002109554,0.0004145603,0.0003013261,0.00008925147,0.00008901776,0.003334306],"genre_scores_gemma":[0.9908864,0.0009235559,0.003970377,0.0002520765,0.0001412177,0.00002233344,0.0001143029,0.00002939336,0.00366035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7019268,"threshold_uncertainty_score":0.5978295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0121096398317694,"score_gpt":0.2418908974974867,"score_spread":0.2297812576657173,"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."}}