{"id":"W2271082097","doi":"10.1016/j.chembiol.2015.12.009","title":"Chemical Biology Approaches to Genome Editing: Understanding, Controlling, and Delivering Programmable Nucleases","year":2016,"lang":"en","type":"review","venue":"Cell chemical biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; Howard Hughes Medical Institute","keywords":"Genome editing; Transcription activator-like effector nuclease; Computational biology; Computer science; CRISPR; Genome; Biology; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008010609,0.001199942,0.001328935,0.001522839,0.000284506,0.00116875,0.001600164,0.001406278,0.002505834],"category_scores_gemma":[0.0008148782,0.0003831762,0.0004312733,0.001564171,0.001049829,0.001436771,0.0009299332,0.002390422,0.001737072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008871073,"about_ca_system_score_gemma":0.001215428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008105738,"about_ca_topic_score_gemma":0.001674953,"domain_scores_codex":[0.9996752,0.00003879243,0.00002654573,0.00005880654,0.0001628671,0.00003779278],"domain_scores_gemma":[0.9996544,0.0001908999,0.00004689451,0.00001590086,0.00006042636,0.00003143416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005945116,0.00006239823,0.0001052129,0.01151483,0.00007588026,0.0002196055,0.00005992413,0.0006428825,0.01370724,0.01681597,0.02642012,0.9303165],"study_design_scores_gemma":[0.00001143006,0.00004199158,0.0001695146,0.0009790105,0.00005287105,0.0008019226,0.00002818961,0.0001310455,0.005146018,0.003709001,0.9889057,0.00002329991],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001808399,0.9948305,0.002253974,0.0004654361,0.0004114367,0.000008023485,0.00001876167,0.00002869451,0.001802184],"genre_scores_gemma":[0.001401715,0.9954868,0.001183661,0.0002988399,0.0001731369,0.0000111171,0.00003589344,0.000006007842,0.001402758],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002505834,"threshold_uncertainty_score":0.008382857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06690512022250163,"score_gpt":0.3134690772928986,"score_spread":0.246563957070397,"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."}}