Individual Response to Standardized Exercise
Bibliographic record
Abstract
PURPOSE: (1) Determine the effect of exercise amount and intensity on the proportion of adipose tissue (AT) responses likely, very likely, and unlikely above the minimal clinically important difference (MCID); and (2) Examine whether clinically meaningful anthropometric changes reflect individual AT responses above the MCID. METHODS: Men (n=41) and women (n=62) (52.7 ± 7.6 years) were randomized to control (N=20); low amount low intensity (LALI, N=24); high amount low intensity (HALI, N=30); and high amount high intensity (HAHI, N=29) exercise for 24 weeks. AT changes were measured by MRI. The probability that individual responses were > MCID after adjusting for technical error of measurement were calculated for each individual and categorized as: 'Unlikely' = < 25%, 'Possibly' = 25-74%, 'Likely' = 75-94%, 'Very Likely' = 95-100% chance. RESULTS: The HALI (total AT) and HAHI (total AT, visceral AT) groups had a greater proportion of individuals whose response was "very likely" ≥ MCID vs controls (p<0.006). Across the abdominal AT depots, for individuals who reduced WC or body weight ≥ 2 cm or 2 kg, respectively, 51-69% of responses were "likely" or "very likely" beyond the MCID. CONCLUSION: Increasing exercise amount and/or intensity may increase the proportion of individuals deemed 'very likely' to achieve clinically meaningful AT reductions. The use of anthropometric change to identify individual response for adiposity reduction remains a challenge.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".