{"id":"W2479285410","doi":"10.1128/aem.02128-16","title":"Extending CRISPR-Cas9 Technology from Genome Editing to Transcriptional Engineering in the Genus Clostridium","year":2016,"lang":"en","type":"article","venue":"Applied and Environmental Microbiology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centurion Biofuels (Canada); University of Waterloo","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Government of Canada","keywords":"CRISPR; Genome editing; Biology; Genome; Genetics; Computational biology; Cas9; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000810229,0.000150292,0.0001170302,0.00006573073,0.00004390685,0.00000675793,0.000155117,0.0001495529,0.0000334825],"category_scores_gemma":[0.000007548518,0.0001087433,0.00002881775,0.00004645368,0.0000700259,0.000002028783,0.00009426645,0.00008285432,0.00001719232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002092312,"about_ca_system_score_gemma":0.000003733754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004860804,"about_ca_topic_score_gemma":0.000005639516,"domain_scores_codex":[0.9991929,0.00001088366,0.0001551754,0.0003371833,0.00002799589,0.0002758817],"domain_scores_gemma":[0.9997516,0.00001850796,0.00002518291,0.000164514,0.000001343786,0.00003882069],"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":[0.00001315464,0.00001641596,0.001101029,0.000002365041,0.00001499985,0.000002899905,0.00006707462,0.00009516102,0.9950455,0.00009082509,0.00005124855,0.003499369],"study_design_scores_gemma":[0.001053029,0.0001665053,0.02362099,0.00001394441,0.00001643549,0.0001198333,0.0004406313,0.000008915068,0.8674285,0.00006784022,0.1067231,0.0003402709],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894876,0.0009777721,0.008697534,0.0004228452,0.00008698316,0.0001627954,0.0001076208,0.00001049189,0.00004639123],"genre_scores_gemma":[0.9983755,0.0001999636,0.000738884,0.0002421243,0.0002315564,0.00004891781,0.000127028,0.00001677588,0.00001926988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.127617,"threshold_uncertainty_score":0.4434423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002988185360314819,"score_gpt":0.1948008756512281,"score_spread":0.1918126902909133,"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."}}