{"id":"W4405896537","doi":"10.1073/pnas.2413519121","title":"Mechanism-guided engineering of a minimal biological particle for genome editing","year":2024,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Livermore National Laboratory; National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; Parker Institute for Cancer Immunotherapy; Alexander von Humboldt-Stiftung; National Cancer Institute; National Institutes of Health; National Heart, Lung, and Blood Institute; European Molecular Biology Organization","keywords":"Genome editing; Cas9; Ribonucleoprotein; Genome; Computational biology; CRISPR; Capsid; Genome engineering; Guide RNA; Biology; Cell biology; Computer science; Gene; RNA; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003356957,0.0003327768,0.0002325216,0.0002086729,0.0002328348,0.0005412256,0.0004266906,0.0004736617,0.0006200449],"category_scores_gemma":[0.0002696439,0.0002749987,0.0003200931,0.0001216949,0.0003509462,0.0002523233,0.0004013486,0.0007277951,0.0003296957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007452488,"about_ca_system_score_gemma":0.0004531434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005163759,"about_ca_topic_score_gemma":0.0007578065,"domain_scores_codex":[0.9998424,0.00002147264,0.00001664542,0.0000292092,0.00006241482,0.00002777637],"domain_scores_gemma":[0.9999027,0.00001693071,0.00003023232,0.00001307119,0.00001758615,0.00001928825],"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":[0.0000309333,0.00002395084,0.0001214034,0.00005419553,0.000007849033,0.00007038972,0.0000254563,0.001727881,0.9925351,0.003036414,0.0001140631,0.002252527],"study_design_scores_gemma":[0.00001833647,0.0001213799,0.0003243613,0.000009953616,0.000009259864,0.0001283877,0.00001729177,0.008551614,0.9810378,0.0004055514,0.00936673,0.000009347606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7177883,0.001172332,0.2710468,0.0004824041,0.0002284274,0.000458219,0.00077492,0.0006919138,0.007356564],"genre_scores_gemma":[0.8658891,0.0006332874,0.1280544,0.00009747677,0.000009122842,0.0002729755,0.0007513753,0.0001270139,0.00416528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007452488,"threshold_uncertainty_score":0.005407214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03871776268091414,"score_gpt":0.334167478632959,"score_spread":0.2954497159520449,"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."}}