Bibliographic record
Abstract
Metal corrosion is usually a bad thing, but in some instances it can be beneficial, even therapeutic. For example, scientists have been developing biodegradable metal alloys that appear to promote healing when used as replacements for conventional noncorrosive metal pins and screws used to fix broken bones. A team of South Korean and Canadian researchers has now shown how magnesium screws laced with calcium and zinc—elements known to promote bone health—help heal small fractures in hands and wrists (Proc. Natl. Acad. Sci. USA 2016, DOI: 10.1073/pnas.1518238113). Using a variety of techniques, including fluorescence microscopy and energy-dispersive X-ray spectroscopy, the team tracked the water-driven degradation of screws inside patients at Ajou University Hospital for several months. A by-product of this degradation, magnesium hydroxide, spurs calcium phosphate formation near the screw. This activity, in turn, helps induce bone growth, says team member Hyung-Seop Han of the Korea Institute of Science & Technology.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.123 | 0.051 |
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".