Bibliographic record
Abstract
Aerobic exercise has consistently been shown to improve glucose control (1–3), enhance insulin sensitivity (2,4,5), and improve cardiovascular risk factors such as visceral adiposity (2), lipid profile (6), arterial stiffness (7), and endothelial function (8). Consistent with this evidence, the American Diabetes Association (ADA) recommends that individuals with type 2 diabetes perform at least 150 min of moderate-intensity aerobic exercise and/or at least 90 min of vigorous aerobic exercise per week (9). Although a lifestyle modification of this nature could have substantial impact on the metabolic and cardiovascular health of this population, it is often difficult for those who have been habitually sedentary to adhere to these guidelines. Indeed, a recent population-based study found that only 28% of individuals with type 2 diabetes achieve these recommendations (10). Unfortunately, it is frequently those who would benefit the most from aerobic exercise that have the greatest difficulty performing it. For individuals with severe obesity, arthritis, physical disabilities, and/or diabetes complications, even walking for 20–30 min may be challenging, uncomfortable, and/or painful to perform. With the continued increase in the prevalence of type 2 diabetes (11), it is evident that alternate forms of physical activity that produce similar metabolic improvements to aerobic exercise may be beneficial in the management of this disease. Resistance training has recently been recognized as a useful therapeutic tool for the treatment of a number of chronic diseases (12–19) and has been demonstrated to be safe and efficacious for the elderly (20,21) and obese (22) individuals. Similar to aerobic exercise, resistance training has been reported to enhance insulin sensitivity (23–25), daily energy expenditure (26,27), and quality of life (20,28). Furthermore, resistance training has the potential for increasing muscle strength (13,29, …
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".