{"id":"W2769039165","doi":"10.1242/jcs.206854","title":"Quantitative analysis of multilayer organization of proteins and RNA in nuclear speckles at super resolution","year":2017,"lang":"en","type":"article","venue":"Journal of Cell Science","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":332,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Searle Scholars Program; University of Washington; Howard Hughes Medical Institute; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Carle Foundation Hospital; American Cancer Society; National Institutes of Health; National Science Foundation","keywords":"Biology; RNA; Computational biology; Resolution (logic); Cell biology; Genetics; Artificial intelligence; Gene; Computer science","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":[0.0002377833,0.0001579236,0.0001858298,0.0005146622,0.0001264997,0.0002833731,0.0001946204,0.0001907575,0.0006161685],"category_scores_gemma":[0.0003420811,0.0002176114,0.0002126885,0.0002589392,0.00024092,0.0003368613,0.0001843183,0.000307475,0.0001021002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000357519,"about_ca_system_score_gemma":0.0001126378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000667917,"about_ca_topic_score_gemma":0.0005278579,"domain_scores_codex":[0.9999132,0.00001101355,0.000003720878,0.00001965407,0.00003121297,0.00002115588],"domain_scores_gemma":[0.999576,0.0001580076,0.00008726033,0.00004421105,0.00008134518,0.00005311178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000925503,0.00002707663,0.002363827,0.00004580951,0.00002844562,0.00008316117,0.00004092292,0.01314852,0.9810096,0.0006520153,0.00005907051,0.002449112],"study_design_scores_gemma":[0.000015824,0.000120795,0.04718811,0.00001112234,0.00004124039,0.0001850096,0.00007354264,0.5077791,0.4432591,0.0008532109,0.0004323776,0.00004055477],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711604,0.0001502793,0.02778703,0.00002347885,0.000006226736,0.00001063618,0.0001304074,0.0001859067,0.000545472],"genre_scores_gemma":[0.9889423,0.00008404688,0.01060054,0.000008392973,0.00000406503,0.0000116981,0.0001121713,0.00002942208,0.0002073425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000667917,"threshold_uncertainty_score":0.002594054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668313378163029,"score_gpt":0.3009640317926542,"score_spread":0.2842808980110239,"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."}}