Bibliographic record
Abstract
Tendons are often affected by chronic pain and rupture, particularly in the middle-aged and elderly, but also in the sporting and physically active younger population. Although not life threatening, these conditions (‘tendinopathy’) are major causes of morbidity, and estimated to cost tens of millions of pounds every year in lost productivity. I have previously shown that the organisation and composition of the tendon extracellular matrix (ECM) are substantially altered in tendinopathy, and that these changes may predispose to tendon pain and rupture. I have also shown that most tendinopathy is degenerative, with changes in fibroblast activity and increased ECM turnover. ECM degradation, in both normal physiology and pathology, is largely mediated by metalloproteinase enzymes: the matrix metalloproteinases (MMP) and the ‘A Disintegrin And Metalloproteinase with ThromboSpondin motifs’ (ADAMTS). I have previously shown that there are differences in MMP activity in chronic tendinopathy compared to acute tendon injuries, as well as differences in collagen turnover between tendons. Thus, although it is not known which enzymes are implicated, perturbation of the balance of metalloproteinase activities is a potential cause of tendinopathy.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".