{"id":"W2800773898","doi":"10.1016/j.cell.2018.03.052","title":"An Integrated Genome-wide CRISPRa Approach to Functionalize lncRNAs in Drug Resistance","year":2018,"lang":"en","type":"article","venue":"Cell","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":332,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Montreal Clinical Research Institute","funders":"Common Fund; National Cancer Institute; Ludwig Center at Harvard; National Institutes of Health; Harvard T.H. Chan School of Public Health; NIH Office of the Director; European Molecular Biology Organization; Università degli Studi di Torino; Fulbright Association; National Human Genome Research Institute; Burroughs Wellcome Fund","keywords":"Biology; GAS6; CRISPR; Gene; Myeloid leukemia; Long non-coding RNA; Computational biology; Genome; Drug resistance; Functional genomics; Genetics; Cancer research; Genomics; RNA; Signal transduction","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003130757,0.0001666386,0.0001321233,0.0001228896,0.00007585439,0.00004138894,0.0003560492,0.0001542984,0.000110201],"category_scores_gemma":[0.00007287368,0.0001716907,0.00005287059,0.0003639649,0.00007876559,0.000005091406,0.0001057183,0.0001876232,0.0001188045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008355526,"about_ca_system_score_gemma":0.0001809962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009550085,"about_ca_topic_score_gemma":0.0005163947,"domain_scores_codex":[0.9984834,0.0001270819,0.0001960271,0.0005951743,0.0002181717,0.0003801868],"domain_scores_gemma":[0.9989693,0.000007799015,0.00003907049,0.0005887321,0.0002079028,0.0001872327],"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":[0.0003363438,0.0001615409,0.00003099921,0.00002001402,0.00001451514,0.000005840399,0.0001530666,0.0002735014,0.9828164,0.00007425539,0.01593965,0.0001738525],"study_design_scores_gemma":[0.0004834191,0.00015826,0.0003705018,0.000008945471,0.000005049174,0.000002279273,0.0001497936,0.0001034329,0.550678,0.00006720313,0.447767,0.0002061018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.571343,0.001642982,0.3278835,0.0003907451,0.0004513163,0.001044108,0.00004748266,0.00006167162,0.09713514],"genre_scores_gemma":[0.9737474,0.00005566453,0.006635559,0.0008640509,0.000266679,0.00008424363,0.0002823561,0.00005078647,0.01801323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4321384,"threshold_uncertainty_score":0.7001345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00995856221809219,"score_gpt":0.2580276015382662,"score_spread":0.248069039320174,"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."}}