{"id":"W3152355149","doi":"10.71781/28874","title":"An analysis of translation heterogeneity in ribosome profiling data","year":2019,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Translation (biology); Profiling (computer programming); Ribosome profiling; Computational biology; Computer science; Biology; Genetics; Messenger RNA","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003756691,0.000923137,0.001131645,0.005105168,0.0009801969,0.002310816,0.0006764389,0.001122174,0.001279487],"category_scores_gemma":[0.01324748,0.0003696989,0.001462476,0.007327345,0.0003542102,0.001007118,0.0008958615,0.0009569228,0.002170929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118693,"about_ca_system_score_gemma":0.001114915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003302834,"about_ca_topic_score_gemma":0.004742496,"domain_scores_codex":[0.9946967,0.0007441785,0.000733938,0.001504187,0.00185259,0.0004682856],"domain_scores_gemma":[0.9913341,0.003599462,0.001330584,0.001720101,0.001690332,0.000325446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003597935,0.0005878988,0.2249317,0.001998394,0.001445779,0.00368551,0.0009415179,0.02037077,0.2927104,0.004496977,0.0482551,0.3969781],"study_design_scores_gemma":[0.0002018125,0.0007135393,0.4655969,0.0003339931,0.0006149029,0.004320966,0.001213506,0.3095916,0.1262613,0.006974611,0.08384237,0.0003345472],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7914241,0.00508993,0.09122375,0.001193557,0.0008690832,0.0004365605,0.08740504,0.01621022,0.006147707],"genre_scores_gemma":[0.7551811,0.001081446,0.08127827,0.0004217127,0.0003084029,0.0003668748,0.156729,0.001487585,0.003145546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005105168,"threshold_uncertainty_score":0.01986748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07062474196655795,"score_gpt":0.3648916680326159,"score_spread":0.2942669260660579,"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."}}