{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005012184,0.0001864962,0.0001657721,0.00005036725,0.00007393004,0.00002881776,0.000209962,0.0001587596,0.00007163232],"category_scores_gemma":[0.0006638167,0.0001757995,0.000104044,0.00008470727,0.00008415755,0.000002381572,0.000111942,0.0002273089,0.000009318606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003761518,"about_ca_system_score_gemma":0.00002418904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003500565,"about_ca_topic_score_gemma":0.00004344766,"domain_scores_codex":[0.9989775,0.0001236954,0.0002023687,0.0003596807,0.00007075759,0.0002660281],"domain_scores_gemma":[0.9992731,0.0001018152,0.00003777441,0.0004413226,0.00003707438,0.0001088678],"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":[0.00001648653,0.00004835806,0.003973879,0.00002044549,0.00003651064,0.000001687257,0.00009638684,0.0002546725,0.8948376,0.00003769802,0.0003102797,0.100366],"study_design_scores_gemma":[0.0005026741,0.0001573465,0.006186683,0.000007329827,0.00002503479,0.00003054329,0.0002530373,0.003991079,0.9497415,0.0004188517,0.03837122,0.0003146547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7160895,0.0008496958,0.2808924,0.00004808336,0.0005496821,0.0001373316,0.000009514953,0.00003772944,0.001386088],"genre_scores_gemma":[0.6488619,0.00003526086,0.350492,0.0000344108,0.0001033879,0.00003306141,0.00003538133,0.00002238675,0.0003821132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1000514,"threshold_uncertainty_score":0.7168896,"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."}}