{"id":"W3034852933","doi":"10.1038/s41587-020-0587-z","title":"Publisher Correction: Engineered CRISPR–Cas12a variants with increased activities and improved targeting ranges for gene, epigenetic and base editing","year":2020,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"CRISPR; Genome editing; Epigenetics; Computational biology; Biology; Genetics; Gene","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":[0.002136779,0.001825787,0.002082367,0.003250926,0.002847337,0.00382655,0.004240862,0.006922767,0.07745184],"category_scores_gemma":[0.02406858,0.001351559,0.001391327,0.002655638,0.002008331,0.002299748,0.001894088,0.008322923,0.03956807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002901713,"about_ca_system_score_gemma":0.003217729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007112432,"about_ca_topic_score_gemma":0.007808364,"domain_scores_codex":[0.9966998,0.0003379383,0.0004989418,0.0006054798,0.001564118,0.0002937744],"domain_scores_gemma":[0.983707,0.002800034,0.001237856,0.002464236,0.008988268,0.0008025918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008624862,0.00001305004,0.0001471368,0.0003746003,0.00004142072,0.001080287,0.00004994277,0.0002063668,0.001061549,0.002894961,0.9751465,0.01889785],"study_design_scores_gemma":[0.0000382105,0.00002322243,0.0006279667,0.0001744818,0.00006881393,0.001776822,0.00004467161,0.0004187684,0.003803533,0.001513858,0.9914632,0.00004631788],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0009571479,0.001936816,0.005772134,0.02500015,0.9529852,0.0000368185,0.002750138,0.001889262,0.008672324],"genre_scores_gemma":[0.06325639,0.009923538,0.02705975,0.03328916,0.1571766,0.0003214249,0.0116264,0.00628643,0.6910604],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.07745184,"threshold_uncertainty_score":0.2591022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003451073510145323,"score_gpt":0.2251285054414667,"score_spread":0.2216774319313214,"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."}}