{"id":"W2784370070","doi":"10.1016/j.molcel.2017.12.020","title":"High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies","year":2018,"lang":"en","type":"article","venue":"Molecular Cell","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":820,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Jewish General Hospital; McGill University; SickKids Foundation; University of Toronto; Sinai Health System; Montreal Clinical Research Institute; Lunenfeld-Tanenbaum Research Institute","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Government of Ontario; Canada Research Chairs; Canada Foundation for Innovation; Canadian Institutes of Health Research","keywords":"Biology; Messenger RNA; Translation (biology); Cell biology; Stress granule; Core protein; RNA-binding protein; RNA; P-bodies; Rna processing; Ribonucleoprotein; Precursor mRNA; RNA splicing; Molecular biology; Genetics; 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":[0.0001927311,0.0001734414,0.0002228896,0.0004343896,0.0006117705,0.001089829,0.0003931488,0.0004408382,0.001926505],"category_scores_gemma":[0.0003393519,0.0002372346,0.0002486614,0.0003785121,0.0003981607,0.0007494036,0.0005842742,0.0008141886,0.001057438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003737664,"about_ca_system_score_gemma":0.0002023909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006668043,"about_ca_topic_score_gemma":0.001247878,"domain_scores_codex":[0.9998813,0.00001540835,0.000006633604,0.00004296926,0.00003288484,0.00002077435],"domain_scores_gemma":[0.9996723,0.000122577,0.00005296596,0.00004866217,0.0000393975,0.00006413069],"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":[0.0001805449,0.00002109743,0.0006840685,0.00004299203,0.000007576235,0.00010371,0.00006968332,0.00008519145,0.9931456,0.001510946,0.00009779225,0.004050836],"study_design_scores_gemma":[0.00004692756,0.0001437299,0.04062987,0.00001859993,0.00004124465,0.001864646,0.0002997702,0.005033107,0.9427412,0.002893228,0.006266662,0.00002095053],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631408,0.002629522,0.02894995,0.0004871171,0.00004376732,0.0000156697,0.0003053592,0.000123234,0.004304573],"genre_scores_gemma":[0.9816311,0.00064301,0.01313601,0.00006922138,0.00003397178,0.00001666072,0.0004351209,0.00005059696,0.003984396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001926505,"threshold_uncertainty_score":0.006444812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007705005522753465,"score_gpt":0.2118725875610718,"score_spread":0.2041675820383183,"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."}}