{"id":"W2577803396","doi":"10.1128/msphere.00340-16","title":"Optimized CRISPR-Cas9 Genome Editing for <i>Leishmania</i> and Its Use To Target a Multigene Family, Induce Chromosomal Translocation, and Study DNA Break Repair Mechanisms","year":2017,"lang":"en","type":"article","venue":"mSphere","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Government of Canada","keywords":"Biology; CRISPR; Genome editing; Cas9; Genetics; Gene; Guide RNA; Recombinase; Homologous recombination","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":[0.0002033236,0.0002165693,0.0002250709,0.00001964566,0.0003382872,0.0001358102,0.000176338,0.0001300741,0.0000074242],"category_scores_gemma":[0.0001498773,0.0002265073,0.00006021854,0.00002736852,0.00002247781,0.00001738235,0.0001421302,0.00006663568,0.000001377076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008530268,"about_ca_system_score_gemma":0.00002713106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006793137,"about_ca_topic_score_gemma":0.0001283846,"domain_scores_codex":[0.998857,0.00002416767,0.0002222273,0.0005207236,0.00009792321,0.0002779663],"domain_scores_gemma":[0.9992096,0.0000148644,0.00007046269,0.0004247052,0.0001240849,0.000156311],"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":[0.0000913826,0.00008130658,0.0003816493,0.00005304048,0.00009801899,0.000009066075,0.0004183992,0.0009006617,0.9966689,0.00001652749,0.0002621402,0.001018952],"study_design_scores_gemma":[0.007838429,0.001919375,0.05895419,0.00008507027,0.0001895261,0.00008622566,0.002178082,0.007657144,0.8975139,0.00006370059,0.02228357,0.001230826],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9425665,0.001145642,0.05487424,0.00009937938,0.0001714481,0.0009840684,0.00008113397,0.00003530637,0.00004232542],"genre_scores_gemma":[0.9674834,0.00009250866,0.03152858,0.0001492566,0.0002915651,0.0001532615,0.00003980389,0.00004538107,0.0002162539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09915499,"threshold_uncertainty_score":0.9236701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01774999224538712,"score_gpt":0.2934497100654763,"score_spread":0.2756997178200892,"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."}}