{"id":"W2128220972","doi":"10.1101/gr.162230.113","title":"Identifying mRNA sequence elements for target recognition by human Argonaute proteins","year":2014,"lang":"en","type":"article","venue":"Genome Research","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Argonaute; Biology; RNA; microRNA; RNA-binding protein; Gene silencing; Computational biology; Messenger RNA; RNA-induced silencing complex; Genetics; RNA silencing; RNA interference; Gene","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":[0.0002142118,0.0002593095,0.0002524658,0.0003286955,0.0002019599,0.0002405738,0.0001539578,0.0002505288,0.0007499501],"category_scores_gemma":[0.000426604,0.0002240486,0.0002932148,0.0001697684,0.0001331033,0.0001001141,0.0001452641,0.0002015359,0.0004811012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001945545,"about_ca_system_score_gemma":0.0002055224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004899674,"about_ca_topic_score_gemma":0.001375026,"domain_scores_codex":[0.9998499,0.00003579177,0.00001087639,0.00003665348,0.00004417962,0.00002258858],"domain_scores_gemma":[0.9998327,0.0000750805,0.00002771728,0.00001486537,0.00001899437,0.0000305892],"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":[0.0001296263,0.00001988583,0.003017538,0.00003815952,0.00000950315,0.00008493693,0.00002441683,0.0002586178,0.9940549,0.0001497442,0.00004047478,0.002172314],"study_design_scores_gemma":[0.00002038945,0.000295343,0.04988351,0.00001525391,0.00003724689,0.0008446029,0.0000590638,0.009191668,0.9360992,0.0003472194,0.003189233,0.00001714987],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917518,0.000704138,0.006490444,0.00002668579,0.000006827012,0.00001819773,0.0001929874,0.00005608251,0.0007527783],"genre_scores_gemma":[0.9852955,0.0002616057,0.01273259,0.00004364444,0.000009012028,0.00002363036,0.0009597808,0.00001526228,0.0006589331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007499501,"threshold_uncertainty_score":0.002508819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161097859879423,"score_gpt":0.4046512644890861,"score_spread":0.2885414785011438,"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."}}