{"id":"W2895140123","doi":"10.1534/g3.118.200461","title":"Double Selection Enhances the Efficiency of Target-AID and Cas9-Based Genome Editing in Yeast","year":2018,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO","funders":"Canadian Institutes of Health Research","keywords":"Genome editing; CRISPR; Selection (genetic algorithm); Multiplex; Cas9; Computational biology; Computer science; Biology; Genetics; Gene; Artificial intelligence","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":[0.0002399071,0.0001789195,0.0001594873,0.00008258539,0.0001066058,0.00002302178,0.0002065542,0.0001100875,0.00002238644],"category_scores_gemma":[0.000005465714,0.0001552544,0.00005166906,0.0002233797,0.0001891533,0.000002515899,0.0001011819,0.00007100939,0.000003920208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001356869,"about_ca_system_score_gemma":0.00007809031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000252805,"about_ca_topic_score_gemma":0.0001963887,"domain_scores_codex":[0.9988863,0.00003341718,0.0002869804,0.0003346052,0.0001397435,0.0003189936],"domain_scores_gemma":[0.9994568,0.00001053709,0.00009203083,0.0002720221,0.0001106626,0.00005791814],"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":[0.00003888052,0.00003049751,0.007818299,0.00004016811,0.00001951947,5.713584e-7,0.0002565428,0.007475369,0.9605018,0.000007853443,0.0000175551,0.02379292],"study_design_scores_gemma":[0.0005602033,0.000352563,0.003032474,0.000009653178,0.00001680024,0.00001096322,0.0001851456,0.003480745,0.9463746,0.00001596557,0.04576674,0.0001941328],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8723384,0.1111247,0.01571602,0.0000426832,0.0002343089,0.0002368534,0.00001263037,0.00001014226,0.0002842593],"genre_scores_gemma":[0.9899684,0.005198268,0.003933086,0.00005305693,0.0006804387,0.0000202658,0.00002249978,0.00002661992,0.00009734683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.11763,"threshold_uncertainty_score":0.6331092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007028226109623308,"score_gpt":0.2672020532728505,"score_spread":0.2601738271632272,"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."}}