{"id":"W2160730143","doi":"10.1038/emboj.2012.204","title":"Arabidopsis Argonaute MID domains use their nucleotide specificity loop to sort small RNAs","year":2012,"lang":"en","type":"article","venue":"The EMBO Journal","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Research Council Canada; Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Boehringer Ingelheim Fonds; University of Saskatchewan; Canadian Light Source","keywords":"Argonaute; Biology; Arabidopsis; Nucleotide; Genetics; RNA; Arabidopsis thaliana; Computational biology; Gene; RNA interference","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":[0.0002386036,0.0002932534,0.0002045247,0.0002382294,0.0003092032,0.000694842,0.000300313,0.0003190396,0.001379868],"category_scores_gemma":[0.0003118618,0.0003062743,0.0002582072,0.0001039379,0.0002959467,0.0005626944,0.0004332297,0.0007045665,0.00118357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004979821,"about_ca_system_score_gemma":0.0001864704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000569457,"about_ca_topic_score_gemma":0.001545756,"domain_scores_codex":[0.9998449,0.00001585304,0.000009200268,0.00004947301,0.00004969924,0.00003087032],"domain_scores_gemma":[0.9997078,0.00005460358,0.00006633386,0.00004697145,0.00004801125,0.00007620708],"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":[0.0001170865,0.000006143022,0.0004870854,0.000008156046,0.000003646903,0.00003473237,0.00001487931,0.00004339331,0.9961802,0.0004741745,0.00008529103,0.002545251],"study_design_scores_gemma":[0.000005238635,0.00003407651,0.002607932,0.000001315699,0.000003765555,0.0001441502,0.00001715283,0.001084777,0.993486,0.0001502862,0.00245889,0.000006419918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729193,0.001123555,0.02220247,0.0001460098,0.00006323568,0.00001927943,0.000188938,0.0006497634,0.002687403],"genre_scores_gemma":[0.9888403,0.0001492344,0.007352309,0.0001115582,0.000009380761,0.000009989511,0.0002266504,0.00008802327,0.003212505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001379868,"threshold_uncertainty_score":0.004616141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03584709382516096,"score_gpt":0.2563795085268697,"score_spread":0.2205324147017087,"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."}}