{"id":"W2112425557","doi":"10.1101/gr.133330.111","title":"RIP-chip-SRM—a new combinatorial large-scale approach identifies a set of translationally regulated bantam/miR-58 targets in <i>C. elegans</i>","year":2012,"lang":"en","type":"article","venue":"Genome Research","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Hôtel-Dieu de Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Universität Zürich; Canadian Institutes of Health Research; Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation; Cancer Research UK; Universiteit Utrecht; Wellcome Trust; Friedrich Miescher Institute for Biomedical Research; Universität Basel","keywords":"Biology; Set (abstract data type); Scale (ratio); Computational biology; Caenorhabditis elegans; Cell biology; Genetics; Gene; Computer science; Physics","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":[0.001969066,0.0002130876,0.0003035378,0.0002209144,0.0001405153,0.00003467388,0.0004983757,0.0003172465,0.0001107455],"category_scores_gemma":[0.00007105496,0.0002247884,0.000119428,0.0003795109,0.0001841367,0.00001832006,0.0002082185,0.000366566,0.00002656611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004013321,"about_ca_system_score_gemma":0.0002910557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001892812,"about_ca_topic_score_gemma":0.0001421195,"domain_scores_codex":[0.9971194,0.0003512576,0.0004407218,0.0004670726,0.000691696,0.0009298949],"domain_scores_gemma":[0.9988238,0.00003232495,0.00007908547,0.0005592807,0.0002439613,0.0002615224],"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":[0.0002592079,0.0005130254,0.009958323,0.0001652284,0.000101933,0.000002706212,0.00654556,0.0004208532,0.9785978,0.0005808395,0.002626403,0.0002281313],"study_design_scores_gemma":[0.007737165,0.000843427,0.1142101,0.0000577457,0.00007759436,0.00003911554,0.002303556,0.0008998619,0.7228449,0.005587731,0.1440843,0.001314461],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984906,0.005572564,0.005934446,0.0002441888,0.0003560977,0.0006299797,0.0001163979,0.00001647942,0.002223897],"genre_scores_gemma":[0.9949853,0.0002748731,0.00176722,0.00003348496,0.0007228811,0.00002440623,0.0006428285,0.00004847308,0.001500564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2557529,"threshold_uncertainty_score":0.9166605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387334031984657,"score_gpt":0.3047764480455172,"score_spread":0.2709031077256707,"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."}}