Bibliographic record
Abstract
The extraordinary increase in diabetes worldwide is a matter of great urgency.Molecular biology and genetic approaches have greatly advanced our understanding of the causes of diabetes and its complications and the development of treatment.Despite these advances, the average age at death of Japanese patients with diabetes is still over 10 years younger than the general population in Japan for the period 1971-2000, although the lifespan of both males and females with diabetes has lengthened with time in parallel with that of the Japanese population.The most frequent cause of death was malignant neoplasia, with vascular disease the second highest in frequency during the period 1991-2000.Moreover, recently it has been well recognized that the prevalence of dementia is higher in diabetic patients than non-diabetic subjects.As a possibility promoting cognitive decline in diabetic state, brain insulin resistance associated from defective insulin signaling is proposed in the recent studies.Coupled with the aging of society, an increase in the number of elderly diabetic patients is inevitable.Therefore, in addition to the prevention and the treatment of diabetes mellitus and its vascular complications, the best treatment for dementia in elderly diabetic patients will be one of the most important issues in diabetes management in the future.From these points of view, the management of diabetes and its related problems are discussed, including the effect of polyol pathway hyperactivity in the pathogenesis of diabetic complications.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.474 | 0.278 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".