Bibliographic record
Abstract
Scientists have reported surprising insights into how mussels make the tough, underwater-curing glue that anchors them to wet rocks and piers. The bivalves’ secret is vanadium. Mussels slowly mix that rare metal, along with iron, into their adhesive proteins in microscopic channels just before they secrete them ( Science 2021, DOI: 10.1126/science.abi9702 ). “It’s like a two-part epoxy, except in a microscale process,” says Matthew Harrington , a chemist at McGill University, referring to the industrial-strength glues composed of a resin and a curing agent that are mixed right before application and cure as the two components react. The mussel glue insight could be important for making medical adhesives that can be applied to wet tissues and to other surfaces, which “most man-made adhesives are pretty terrible at,” Harrington says. To stick to underwater surfaces, mussels secrete proteins that cross-link with one another and adhere to rock surfaces via various
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.016 |
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; both teacher heads agree on what is shown here.
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".