{"id":"W4311840815","doi":"10.1101/2022.12.06.519322","title":"A Binary RNA and DNA Self-Amplifying Platform for Next Generation Vaccines and Therapeutics","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Vancouver General Hospital; University of British Columbia","funders":"Urology Foundation; University of British Columbia","keywords":"Computer science; Flexibility (engineering); Computational biology; Recombinant DNA; DNA vaccination; Plasmid; Binary number; Nanotechnology; DNA; Engineering; Biology; Gene; Mathematics; Genetics; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007533119,0.0004279911,0.0002684749,0.0003125908,0.00026938,0.0006486143,0.0003866988,0.0007225289,0.005483376],"category_scores_gemma":[0.0004951778,0.0002585225,0.0002021705,0.0002210171,0.0003017612,0.0005920993,0.000446797,0.000689887,0.003014402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004815377,"about_ca_system_score_gemma":0.0004040795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002332477,"about_ca_topic_score_gemma":0.0002484854,"domain_scores_codex":[0.9997004,0.0000504223,0.00002213819,0.00004650217,0.0001477436,0.0000327399],"domain_scores_gemma":[0.9998581,0.00002975286,0.0000379542,0.00001810295,0.00003245998,0.0000236092],"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":[0.0001787987,0.00004206805,0.0001379828,0.0002171019,0.000006978328,0.0001317371,0.0000428541,0.0005785199,0.9516562,0.008858263,0.007159963,0.03098942],"study_design_scores_gemma":[0.00006566301,0.0002811618,0.0004536638,0.00001653875,0.00001523599,0.0004162762,0.00002208975,0.006965364,0.8894669,0.0020325,0.1002352,0.00002939383],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3245171,0.0121035,0.5892475,0.009893309,0.006433207,0.001260678,0.004399195,0.01302094,0.03912448],"genre_scores_gemma":[0.5405858,0.004144136,0.3805517,0.001593213,0.0008418902,0.0005345366,0.004586889,0.0008986429,0.06626326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005483376,"threshold_uncertainty_score":0.01834375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743802688309495,"score_gpt":0.2527314980438288,"score_spread":0.2152934711607338,"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."}}