Bibliographic record
Abstract
Although most patients undergo muscle biopsies to elucidate the cause of muscle symptoms (weakess, cramping, etc.), many muscle biopsies show relatively few specific alterations on routine staining. Immunohistochemical methods for muscle fibre typing and characterisation of inflammatory cell infiltrates are now well established but the value of other markers is less well documented. A preliminary study of other potentially useful immunohistochemical markers revealed that muscle biopsies in our hospital often contain CD56 and/or D2-40 positive myofibres. This study was extended to a series of 32 biopsies from adult patients (age 21–81, 12 males 20 females), 11 of which showed only minor changes on routine examination. Most cases contained CD56 positive mature fibres; D2-40 positive muscle fibres were more common in cases of inflammatory myopathy. Five cases with minor changes on routine examination showed CD56 and D2-40 staining of otherwise unremarkable myofibres, which might represent reactive changes. LEARNING OBJECTIVES This presentation will enable the learner to: 1. Describe patterns of immunohistochemical staining in reactive muscle fibres 2. Discuss the underlying physiology of reactive muscle fibres
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".