{"id":"W1605296364","doi":"10.21083/surg.v3i1.1026","title":"A bioinformatics approach to defining the AU-Rich Element (AURE) Identification of novel motifs flanking AU-Rich Elements","year":2009,"lang":"en","type":"article","venue":"SURG Journal","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Untranslated region; Perl; Computational biology; Gene; Biology; Genetics; Three prime untranslated region; Identification (biology); Messenger RNA; Computer science; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001844622,0.0001255982,0.0001393645,0.0001131331,0.0003017897,0.00009820836,0.0003668368,0.00006204294,0.000005268683],"category_scores_gemma":[0.0001637481,0.00009077692,0.00008391049,0.0002168718,0.00002654998,0.00001370917,0.00008324841,0.0001942147,0.000005771431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008003451,"about_ca_system_score_gemma":0.0002341975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001696686,"about_ca_topic_score_gemma":0.00001141605,"domain_scores_codex":[0.9983013,0.00005781702,0.0006125901,0.0001485082,0.0004498216,0.0004299791],"domain_scores_gemma":[0.9990851,0.00001601514,0.0002976673,0.000278971,0.0001897449,0.0001324848],"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":[0.0001196981,0.0003414216,0.02264793,0.00004512489,0.0001823007,0.000002171079,0.001597916,0.003308538,0.9184613,0.0004556877,0.002495819,0.05034209],"study_design_scores_gemma":[0.00708948,0.002586347,0.1374177,0.0003674983,0.0002203833,0.0007032658,0.01188719,0.07360857,0.7471912,0.0003853494,0.01703051,0.001512507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9173729,0.0001688776,0.08015905,0.0002485324,0.0001025167,0.0001956862,0.000009260885,0.000003991031,0.001739114],"genre_scores_gemma":[0.9922954,0.00006828777,0.006908754,0.0001843207,0.0002225029,0.000006440664,0.00004299722,0.00001002322,0.0002612404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1712701,"threshold_uncertainty_score":0.3701775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924482597449621,"score_gpt":0.287154090598396,"score_spread":0.2679092646238998,"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."}}