{"id":"W2340356391","doi":"10.1038/gt.2016.36","title":"Development of an AAV9 coding for a 3XFLAG-TALEfrat#8-VP64 able to increase in vivo the human frataxin in YG8R mice","year":2016,"lang":"en","type":"article","venue":"Gene Therapy","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec","funders":"","keywords":"Biology; Frataxin; In vivo; Transcription (linguistics); Molecular biology; Gene; Effector; Haploinsufficiency; Gene expression; Messenger RNA; Activator (genetics); Transcription activator-like effector nuclease; Cell biology; Genetics; Genome editing; CRISPR; Iron-binding proteins","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":[0.0003087378,0.0006460318,0.0003176805,0.0005135951,0.0001871532,0.0002870253,0.0004615654,0.0006799511,0.001929488],"category_scores_gemma":[0.000137415,0.0003231098,0.0004892712,0.0001325659,0.00037984,0.0003141521,0.0003047521,0.001011687,0.0008123183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002972548,"about_ca_system_score_gemma":0.0002559415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005405294,"about_ca_topic_score_gemma":0.0005084046,"domain_scores_codex":[0.9997231,0.00003419496,0.00003824463,0.00008556843,0.00007745709,0.00004137093],"domain_scores_gemma":[0.999814,0.00002737513,0.00008001737,0.00001778063,0.0000160915,0.00004477127],"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":[0.00002550397,0.00002236584,0.00003893381,0.00002030447,0.000004001654,0.00004981747,0.00001215827,0.00005291867,0.9988999,0.0001340851,0.00002328116,0.0007166335],"study_design_scores_gemma":[0.00005515296,0.0004928797,0.001107512,0.00001288165,0.00002706193,0.0005970813,0.00001750784,0.001108316,0.9906701,0.00005883165,0.005843417,0.000009337718],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9287204,0.001233198,0.06413168,0.0003114945,0.0001888823,0.0004730414,0.001624172,0.0008852285,0.002432003],"genre_scores_gemma":[0.9034698,0.001457856,0.07566386,0.0001388927,0.00005263001,0.0005609078,0.00328822,0.0003079831,0.01505972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001929488,"threshold_uncertainty_score":0.006454766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01401902917178516,"score_gpt":0.3076732432123441,"score_spread":0.293654214040559,"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."}}