Monographs in Human Genetics Neurofibromatoses. Volume 16. 2008. Edited by Dieter Kaufmann. Published by Karger. 192 pages. Price C$190.
Bibliographic record
Abstract
I will nitpick on a few points.The chapter on alpha-synuclein and PD was well written and referenced, however the conclusion was not a summary but a brief statement of recent advances and did not allow for proper closure.Another chapter had no article titles in the references.There was actually more clinical information on PINK1 parkinsonism in the first chapter on Neuropathology and Staging than in the chapter devoted solely to PINK1 parkinsonism.There is some overlap between the chapters, which isn't necessarily a bad thing.The figures are in black and white which undoubtedly lowers the production cost.While colour photos or figures are nice, the lack of this does not significantly detract from the quality of the book.This book is not intended for a practicing general neurologist.Even for a movement disorders clinician without particular basic science interest, I would suggest reading a review article on genetics and Parkinson's rather than purchasing this book.I recommend "Parkinson's Disease -Genetics and Pathogenesis" for those with a particular interest in basic science, genetics, and animal models and how those interact in PD and PD models.It also makes for a great Neurology library reference book that may inspire future clinician-scientists to further our understanding of Parkinson's.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.125 | 0.085 |
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".