{"id":"W2580375224","doi":"10.1139/gen-2016-0127","title":"Enhancement of single guide RNA transcription for efficient CRISPR/Cas-based genomic engineering","year":2017,"lang":"en","type":"article","venue":"Genome","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Trans-activating crRNA; Guide RNA; Biology; Subgenomic mRNA; Cas9; RNA; Computational biology; Genome editing; RNA polymerase III; Transcription (linguistics); Genetics; DNA; Genome engineering; genomic DNA; RNA polymerase; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001327057,0.0001231815,0.0001290369,0.00003746646,0.00008178403,0.00002277558,0.0002110967,0.00006693614,0.00001160991],"category_scores_gemma":[0.00003626922,0.0001343778,0.0001131526,0.00001424595,0.00002445258,0.000001501668,0.00003356277,0.00002817976,0.000003054275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002703218,"about_ca_system_score_gemma":0.00002710622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009754789,"about_ca_topic_score_gemma":0.000005320403,"domain_scores_codex":[0.9992816,0.000004118477,0.0002052323,0.0002213306,0.00007292602,0.0002147323],"domain_scores_gemma":[0.9993678,0.000004887518,0.00007645813,0.0004444889,0.00005494939,0.00005139528],"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":[0.00002986443,0.00004127008,0.0000154742,0.00007345259,0.0000245316,3.690196e-7,0.00003929283,0.04188108,0.9571772,0.00001064497,0.00002874355,0.0006780846],"study_design_scores_gemma":[0.0005805254,0.0002488373,0.002404664,0.00001329775,0.00002307446,9.977693e-7,0.00001017626,0.003324883,0.967505,0.00000234194,0.02573468,0.000151515],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5598519,0.000613497,0.4389195,0.00004116865,0.0001910086,0.0001866336,0.00002738744,0.000006287064,0.0001626514],"genre_scores_gemma":[0.9919213,0.00002593877,0.007538083,0.00002551538,0.0001665738,0.00003859745,0.00006190881,0.00002469924,0.0001973707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4320695,"threshold_uncertainty_score":0.5479767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01206414875692246,"score_gpt":0.2793240240429447,"score_spread":0.2672598752860222,"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."}}