Fundamentals of Musculoskeletal Pain. 2008. Edited by Thomas Graven-Nielsen, Lars Arendt-Nielsen, Siegfried Mense. Published by IASP Press. 496 pages. Price C$90.
Bibliographic record
Abstract
NEUROLOGIQUES articles analyse the morbidity and mortality of treatment comparing the results with microsurgery versus radiosurgery.Several questions are answered regarding the feasibility of radiosurgery after subtotal microsurgical removal and the need for surgery after gamma knife treatment.Hearing and facial nerve preservation following different modalities of treatment are also analyzed.Discussion of wait and see strategy and the linear accelerator surgery are also discussed together with a special chapter on type II neurofibromatosis and its treatment.The message of this book is clear.It emphasizes the changing trend in the treatment of VS as it relates to the great impact that radiosurgery has made on it.At first glance, the contents of the book appear overwhelming and somewhat repetitive, with two chapters on facial nerve schwannoma.Regardless of these minor controversial points, the book is an excellent reference and will be of great help for neurosurgeons, radiosurgeons and ENT specialists in dealing with the difficult problem arising from the management of VS.
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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.076 | 0.054 |
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".