Long‐range assembly of DNA into nanofibers and highly ordered networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Long‐range assembly of DNA currently comprises both top‐down and bottom‐up methods. The top‐down techniques consist of physical alignment of DNA and lithographic patterning to organize DNA on surfaces. The bottom‐up approaches include lipid‐and polymer–DNA co‐assembly, the self‐assembly of DNA amphiphiles, and the remarkably specific and versatile methods of DNA nanotechnology. DNA‐based materials possess unprecedented molecular control and may offer innovative solutions in the fields of nanotechnology, sensing, nanomedicine, as well as optical and electronic devices. To realize the potential of these materials, a number of hurdles must be addressed. Bridging the gap between top‐down fabrication and bottom‐up assembly is of critical importance to the successful development of functional DNA‐based technology. A profound understanding of both regimes is necessary to achieve this goal. WIREs Nanomed Nanobiotechnol 2013, 5:266–285. doi: 10.1002/wnan.1218 This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it