Bibliographic record
Abstract
Derzeit existiert kein vollständiges und valides System zur Diagnostik der Demenzen. Die Leitlinien des Berufsverbandes der Allgemeinärzte, der Canadian Medical Association und der European Federation of Medical Societies werden vorgestellt und diskutiert. Während die Feststellung des Vorliegens einer Demenz und die Abgrenzung einer Depression einfach sind, bestehen besondere Probleme in der Differenzialdiagnostik der Demenzen untereinander und in der Frühdiagnostik. Es erscheint erforderlich, die einzelnen Konsenskriterien aufeinander abzustimmen und Kriterien für die Differenzialdiagnose festzulegen. Liquoruntersuchungen und MR-Techniken erlauben in naher Zukunft möglicherweise eine positive Diagnose des M. Alzheimer. Consensus Criteria on Diagnosis in Patients with Dementia At present, there is no valid diagnostic system that can be used for the diagnosis of dementia and its underlying causes. The consensus criteria of the German Association of Medical Practicioners, the Canadian Medical Association and the European Federation of Medical Societies are described. While the detection of the presence of dementia and the differential diagnosis towards depression seem relatively easy, there are considerable difficulties in the differential diagnosis among the dementias and in early diagnosis. It is deemed necessary to relate the various diagnostic consensus criteria towards each other and establish consensus for differential diagnosis. CSF analysis and new MR techniques may allow a positive diagnosis of Alzheimer's disease in the near future.
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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.091 | 0.056 |
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".