{"id":"W3090576692","doi":"10.1002/ctm2.194","title":"Improving transgene expression and CRISPR‐Cas9 efficiency with molecular engineering‐based molecules","year":2020,"lang":"en","type":"article","venue":"Clinical and Translational Medicine","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"National Key Research and Development Program of China; Natural Science Foundation of Guangdong Province; Government of Jiangxi Province; National Natural Science Foundation of China","keywords":"CRISPR; Cas9; Transgene; Genome editing; Biology; Gene; Computational biology; Genetic enhancement; Plasmid; Cell biology; Genetics","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":[0.0006030431,0.0007536479,0.0005488769,0.0005295436,0.0002801063,0.0005811822,0.0005133768,0.0006027636,0.0009347715],"category_scores_gemma":[0.0005559521,0.0003186122,0.0004671737,0.0003426436,0.000455455,0.0003844161,0.0004058726,0.001018432,0.0004896477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006064848,"about_ca_system_score_gemma":0.0003695329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004656104,"about_ca_topic_score_gemma":0.0009205898,"domain_scores_codex":[0.9991059,0.0001357512,0.0001363206,0.0002145,0.000306516,0.0001009396],"domain_scores_gemma":[0.999656,0.00007631374,0.0001214651,0.00004331799,0.00005875676,0.00004418938],"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":[0.00001914272,0.00002051175,0.00006990185,0.0000501983,0.000006728999,0.00002465477,0.00000937172,0.0002140913,0.997285,0.0002140648,0.00004463274,0.002041643],"study_design_scores_gemma":[0.000006981583,0.00008352685,0.0002235243,0.000004258941,0.00001464625,0.000071742,0.000004059316,0.001723971,0.9948288,0.0000431019,0.002987405,0.000008043436],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7564146,0.005063806,0.2290762,0.0004744014,0.0002892188,0.0006505116,0.0005088764,0.001695129,0.005827368],"genre_scores_gemma":[0.8366859,0.002309883,0.1548186,0.0001855419,0.00003684467,0.0004460145,0.0005689479,0.0001751114,0.004773133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009347715,"threshold_uncertainty_score":0.004400432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01574441857816584,"score_gpt":0.3119143305036433,"score_spread":0.2961699119254775,"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."}}