{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002940241,0.0004180691,0.0002299884,0.0003853793,0.0001922698,0.000347812,0.0002740021,0.0003406993,0.001306814],"category_scores_gemma":[0.0001764784,0.0001713995,0.0002860141,0.0001876093,0.0003316373,0.000401261,0.0002453885,0.0006631995,0.000551682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003681712,"about_ca_system_score_gemma":0.0004232351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003486061,"about_ca_topic_score_gemma":0.0004789209,"domain_scores_codex":[0.9997706,0.00004088269,0.00002051782,0.00006005626,0.00007692323,0.00003106474],"domain_scores_gemma":[0.9998864,0.00002396712,0.00003359404,0.00001202484,0.00002148745,0.00002252779],"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":[0.00005800218,0.00004342273,0.0001535071,0.0001114448,0.000005660609,0.00007421011,0.00002469975,0.0001345526,0.9876276,0.0006701177,0.0001237036,0.010973],"study_design_scores_gemma":[0.00001921563,0.0005637185,0.0006951959,0.00001472336,0.00004046174,0.000885864,0.00001669636,0.001217344,0.9842268,0.0001574816,0.01214898,0.00001350968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.605583,0.02436328,0.3587878,0.001043494,0.0004604337,0.0006280314,0.0007337087,0.001785748,0.00661456],"genre_scores_gemma":[0.8148598,0.008482372,0.1631573,0.0001897388,0.0000795111,0.0004824871,0.001209306,0.0001234934,0.01141582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001306814,"threshold_uncertainty_score":0.004371703,"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."}}