Dementia in Clinical Practice. Volume 24. Frontiers of Neurology and Neuroscience. 2009. Edited by P. Giannakopoulos, P.R. Hof. Published by Karger. 184 pages. Price C$240 approx.
Bibliographic record
Abstract
The introduction to this book proposes that "new evidences from basic and clinical sciences should be available in a simple and comprehensive form for general practitioners and mental health professionals".That is certainly a laudable goal -the field of dementia is important and confusing, and family physicians, specialists, and even at times neurologists, need some clear up-todate information on how to best diagnose, treat, and manage patients.Family physicians tell us that they desperately need brief and clear guides to diagnosis and therapy.The authors who have been brought together to produce this volume are well-known academics, and work largely in Europe (especially Geneva), but also North America (including Serge Gauthier from Montreal and Andrew Kertesz from London).The approach-separating Alzheimer's Disease, Vascular dementia, Lewy Body dementia, and Frontotemporal dementia as different sections -seems appropriate.Unfortunately, this book fails to live up to its promise.It is not in fact a volume addressed to the needs of general physicians, but a set of chapters focused on the research (and somewhat, the clinical) interests of the authors.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.023 |
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".