Front Cover: Expanding the DOPA Universe with Genetically Encoded, Mussel‐Inspired Bioadhesives for Material Sciences and Medicine (ChemBioChem 17/2019)
Bibliographic record
Abstract
Designing an underwater (“wet”) adhesive is an attractive but challenging task for traditional chemists. Meanwhile, synthetic biology and xenobiology have found solutions based on the natural phenomenon of mussel adhesion. In addition, such bioengineering also provides spatiotemporal control of the strong underwater adhesion and the development of multifunctional modules. Biotechnologically engineered adhesives that can be fused with other modules into one macromolecule will revolutionize materials science, environmental bioremediation and medical care, providing sustainable solutions to long-standing problems such as corrosion or wound healing. Therefore, the biosynthesis of adhesives offers great potential as a disruptive, game-changing technology for materials science and medical applications. More information can be found in the review by N. Budisa et al. on page 2163 in Issue 17, 2019 (DOI: 10.1002/cbic.201900030).
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 teacher head, 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".