Bibliographic record
Abstract
The effects of type 1 and type 2 diabetes on the body's physiological response to thermal stress is a relatively new topic in research. Diabetes tends to place individuals at greater risk for heat-related illness during heat waves and physical activity due to an impaired capacity to dissipate heat. Specifically, individuals with diabetes have been reported to have lower skin blood flow and sweating responses during heat exposure and this can have important consequences on cardiovascular regulation and glycemic control. Those who are particularly vulnerable include individuals with poor glycemic control and who are affected by diabetes-related complications. On the other hand, good glycemic control and maintenance of aerobic fitness can often delay the diabetes-related complications and possibly the impairments in heat loss. Despite this, it is alarming to note the lack of information regarding diabetes and heat stress given the vulnerability of this population. In contrast, few studies have examined the effects of cold exposure on individuals with diabetes with the exception of its therapeutic potential, particularly for type 2 diabetes. This review summarizes the current state of knowledge regarding the impact of diabetes on heat and cold exposure with respect to the core temperature regulation, cardiovascular adjustments and glycemic control while also considering the beneficial effects of maintaining aerobic fitness.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 0.002 |
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".