Bibliographic record
Abstract
A549 cells, engineered, 247 AADC expression, 157 AAV5 capsid vectors, 149.See also Adenoassociated virus (AAV) vectors AAV9 capsid, 131 AAV capsids, 64 variants of, 125 AAV DNA genomes, 62 structures of, 63 AAV serotype 2 (AAV2)-based vectors, 64, 65, 140.See also Ad2/5 serotypes for cystic fibrosis, 148 AAV serotypes, 131 exposure to, 126 AAV vector-mediated delivery, feasibility and efficacy of, 140.See also Ad/AAV hybridbased production method; Adeno-associated virus (AAV) vectors Aβ (amyloid β) levels, reducing, 155 "Accessory" viral genes, 239 Acute cardiovascular event toxicities, 51 Ad2/5 serotypes, 52 Ad35 (group B) fiber vectors, 49 Ad/AAV hybrid-based production method, 248-249 Adaptive immune responses, 170-172 role in eliminating transgene expression, 170-171 Adaptor-based targeting, 224 Adeno-associated virus (AAV) vectors, 61-67, 238.See also AAV entries; Ad/AAV hybrid-based production method; rAAV vectors; Recombinant adeno-associated virus (rAAV) characteristics/properties of, 62, 245-246 elements influencing vector properties, 64 generation of, 62 genome design of, 61-63, 64 immune responses and, 147 for intraarticular RA gene therapy, 140 Concepts in Genetic Medicine, Edited by Boro Dropulic and Barrie Carter
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.688 | 0.599 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".