Muscle temperature transients before, during, and after exercise measured using an intramuscular multisensor probe
Bibliographic record
Abstract
Seven subjects (1 woman) performed an incremental isotonic test on a Kin-Com isokinetic apparatus to determine their maximal oxygen consumption during bilateral knee extensions (Vo(2 sp)). A multisensor thermal probe was inserted into the left vastus medialis (middiaphysis) under ultrasound guidance. The deepest sensor (tip) was located approximately 10 mm from the femur and deep femoral artery (T(mu 10)), with additional sensors located 15 (T(mu 25)) and 30 mm (T(mu 40)) from the tip. Esophageal temperature (T(es)) was measured as an index of core temperature. Subjects rested in an upright seated position for 60 min in an ambient condition of 22 degrees C. They then performed 15 min of isolated bilateral knee extensions (60% of Vo(2 sp)) on a Kin-Com, followed by 60 min of recovery. Resting T(es) was 36.80 degrees C, whereas T(mu 10), T(mu 25), and T(mu 40) were 36.14, 35.86, and 35.01 degrees C, respectively. Exercise resulted in a T(es) increase of 0.55 degrees C above preexercise resting, whereas muscle temperature of the exercising leg increased by 2.00, 2.37, and 3.20 degrees C for T(mu 10), T(mu 25), and T(mu 40), respectively. Postexercise T(es) showed a rapid decrease followed by a prolonged sustained elevation approximately 0.3 degrees C above resting. Muscle temperature decreased gradually over the course of recovery, with values remaining significantly elevated by 0.92, 1.05, and 1.77 degrees C for T(mu 10), T(mu 25), and T(mu 40), respectively, at end of recovery (P < 0.05). These results suggest that the transfer of residual heat from previously active musculature may contribute to the sustained elevation in postexercise T(es).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 0.000 |
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".