{"id":"W1995875746","doi":"10.1016/j.ymeth.2010.12.023","title":"PhiC31 integrase facilitates genetic approaches combining multiple recombinases","year":2010,"lang":"en","type":"article","venue":"Methods","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"","keywords":"Recombinase; Integrase; Site-specific recombination; Genome engineering; Integrases; Computational biology; Homologous recombination; Cre-Lox recombination; Genome; Biology; FLP-FRT recombination; Recombineering; Gene targeting; Genetics; Plasmid; Gene; Transgene; Genome editing; Genetic recombination; Recombination; Genetically modified mouse","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001730175,0.001120588,0.0006469837,0.001064487,0.0007901773,0.001369711,0.00134468,0.001389052,0.004494641],"category_scores_gemma":[0.001015016,0.001398158,0.0005841366,0.0005909444,0.0009379207,0.001003421,0.001411668,0.003283233,0.004064326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007962218,"about_ca_system_score_gemma":0.0008301875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006164851,"about_ca_topic_score_gemma":0.001629935,"domain_scores_codex":[0.9982468,0.0002910078,0.0001868338,0.0003659237,0.0006742391,0.0002351965],"domain_scores_gemma":[0.9989768,0.0002533167,0.0001812166,0.0003526415,0.00007882345,0.0001571125],"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":[0.00005945743,0.00003860959,0.00009317099,0.00007864085,0.000005825803,0.00008134932,0.00003083267,0.00007679928,0.9939857,0.001611214,0.000304023,0.003634442],"study_design_scores_gemma":[0.00001445242,0.00003127405,0.0003407244,0.000008585932,0.000009911872,0.0003545205,0.00001274422,0.0005122486,0.9881582,0.0002087281,0.01033752,0.00001115719],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3026136,0.002862342,0.6639854,0.001881232,0.0007783617,0.001352581,0.002498704,0.00799079,0.01603699],"genre_scores_gemma":[0.6445869,0.003271411,0.3139498,0.0004109634,0.0001314082,0.0007261455,0.00425494,0.001814503,0.03085394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004494641,"threshold_uncertainty_score":0.01503605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04108881499647173,"score_gpt":0.366987012751479,"score_spread":0.3258981977550073,"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."}}