Bibliographic record
Abstract
Abstract Diabetes mellitus (DM) is a metabolic disease affecting the regulation of insulin and glucose causing a disruption in the normal control of counterregulatory hormones and macronutrients, resulting in blood glucose accumulation. Metabolic deregulation leads to the production of noxious substances that have a particular propensity for damaging vascular and nervous structures. Physiological changes observed with aging are correlated with a concomitant increase in DM and its associated complications. Long-term complications, including peripheral and central neuropathies, micro- and macrovascular damage, retinopathy, and nephropathy are the major causes of mortality in diabetics [cardiovascular disease (CVD) being the primary complication causing death in this population]. All-cause mortality is three to four times greater in the DM population; hence, management of DM is of timely importance, particularly with a projected prevalence increase of 134% within the next 25 years among individuals over the age of 65 years. Exercise modalities, including endurance and resistance training, were employed to improve glycemic/metabolic control and to ameliorate the progression of DM-related complications. Several risk factors, including glucose levels, blood pressure, lipid/cholesterol profile, and BMI, are reportedly improved with these modes of exercise. However, not all studies demonstrate an improvement in risk factors, but consistently note improvement in complications and a reduction of DM incidence. There is convincing evidence that exercise, with or without specific improvements to traditional DM-related risk factors, is an effective therapy for the management of DM.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".