{"id":"W1964886860","doi":"10.1371/journal.pone.0047159","title":"A Novel Micro-Linear Vector for In Vitro and In Vivo Gene Delivery and Its Application for EBV Positive Tumors","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Key Research and Development Program of China; King Saud University; National Natural Science Foundation of China; State Key Laboratory in Marine Pollution; Chinese Academy of Sciences; City University of Hong Kong","keywords":"Transfection; Gene delivery; Plasmid; Genetic enhancement; In vivo; Biology; Molecular biology; Viral vector; Vector (molecular biology); In vitro; Electroporation; Expression vector; Gene; Recombinant DNA; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008949944,0.00008631482,0.000126018,0.00004135753,0.0000223286,0.000005528239,0.00004538492,0.0000797919,7.676306e-7],"category_scores_gemma":[0.00003310335,0.0000909277,0.00002059463,0.00003132914,0.00001660159,0.000007682295,0.00003640544,0.00003239918,8.338993e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001179647,"about_ca_system_score_gemma":0.00001629015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001901655,"about_ca_topic_score_gemma":0.00003558281,"domain_scores_codex":[0.99946,0.000008212843,0.0001233386,0.0001953349,0.00003464396,0.0001784466],"domain_scores_gemma":[0.9997631,0.0000194735,0.00003775465,0.00007462757,0.00006168566,0.00004332808],"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":[0.0004927695,0.0003181769,0.001379071,0.00004977956,0.00003223093,1.263059e-7,0.00007468463,0.000001106376,0.9974036,0.000006617525,0.000009685472,0.0002322169],"study_design_scores_gemma":[0.0007828666,0.0001620138,0.004373406,0.0000288464,0.00002189045,0.000002577175,0.00002976983,0.0007313021,0.9937009,0.000007851463,0.0000473074,0.0001113233],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968584,0.001358598,0.0008463412,0.00006779617,0.00001033483,0.0006276097,0.0002183376,0.000002687362,0.000009938475],"genre_scores_gemma":[0.9951695,0.000163892,0.003928921,0.0001640639,0.0001319105,0.0002483666,0.000116905,0.00001258378,0.00006385015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003702689,"threshold_uncertainty_score":0.3707924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02359299611648205,"score_gpt":0.2387822741460371,"score_spread":0.215189278029555,"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."}}