{"id":"W2132508093","doi":"10.15252/embr.201540974","title":"Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network","year":2015,"lang":"en","type":"article","venue":"EMBO Reports","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Stem Cell Network; University of Ottawa; Ottawa Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dello Sviluppo Economico; Ontario Ministry of Economic Development and Innovation; Canadian Institutes of Health Research; Government of Ontario","keywords":"Library science; Embryonic stem cell; Biology; Genetics; 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":[0.0002969305,0.0003367352,0.0002849162,0.0002558927,0.000393296,0.0009093735,0.0007294504,0.0005810601,0.001125871],"category_scores_gemma":[0.0002026723,0.0003708742,0.0003427709,0.0001787822,0.0007054072,0.0005788162,0.0005522202,0.001020758,0.001061559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009895905,"about_ca_system_score_gemma":0.0004383766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007388597,"about_ca_topic_score_gemma":0.001554374,"domain_scores_codex":[0.9997999,0.00002588241,0.00001118823,0.00008303774,0.00005454168,0.00002542098],"domain_scores_gemma":[0.9998498,0.00003684968,0.00003652395,0.00002627347,0.00001198971,0.00003855425],"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":[0.0000819198,0.000005464062,0.0002059852,0.00002065251,0.000003024145,0.00006402271,0.00002600367,0.0002747388,0.9940869,0.002886296,0.00005851351,0.002286565],"study_design_scores_gemma":[0.00001159891,0.00006734687,0.002165133,0.000007829809,0.00002219331,0.0003070648,0.00004829331,0.00393478,0.9853904,0.001502683,0.006530344,0.00001221971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8847973,0.002463972,0.1004539,0.0008716502,0.0001988251,0.00003508812,0.0005435129,0.001066201,0.00956943],"genre_scores_gemma":[0.9626499,0.0007378189,0.03039225,0.0001581363,0.00002738746,0.00001871132,0.0006284278,0.0001650321,0.005222239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001125871,"threshold_uncertainty_score":0.007179976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008985181240264942,"score_gpt":0.2512108500300247,"score_spread":0.2422256687897598,"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."}}