Tissue Temperature Transients in Resting Contra-Lateral Leg Muscle Tissue During Isolated Knee Extension
Bibliographic record
Abstract
This study was designed to evaluate the role of non-active tissue in the retention and dissipation of heat during and following intense isolated muscle activity. Six subjects performed an incremental isotonic test (constant angular velocity, increases in force output) on a KIN-COM isokinetic apparatus to determine their maximal oxygen consumption during single knee extensions (VO2sp). In a subsequent session, a thin wire multi-sensor temperature probe was inserted into the left vastus medialis under ultrasound guidance at a specific internal marker. The deepest temperature sensor (tip, Tmu10) was located approximately 10 mm from the femur and deep femoral artery with 2 additional sensors located at 15 (Tmu25) and 30 (Tmu40) mm from the tip. Implant site was midway between and medial to a line joining the anterior superior iliac spine and base of patella. Esophageal temperature (Tes) temperature was measured as an index of core temperature. Subjects rested in a supine position for 60 min followed by 30 min of seated rest in an ambient condition of 22 degree C. Subjects then performed 15 min of isolated single right knee extensions against a dynamic resistance on a KIN COM corresponding to 60% of VO2sp at 60 degree x sec(-1). Exercise was followed by 60 min of seated rest. Resting Tes was 37 degree C while Tmu10, Tmu25, and Tmu40 were 36.58, 36.55 and 36.45 degree C, respectively. Exercise resulted in a Tes increase of 0.31 C above pre-exercise resting. Tmu of the non-exercising leg increased 0.23, 0.19 and 0.09 degree C for Tmu10, Tmu25, and Tmu40, respectively. While Tes decreased to baseline values within approximately 15 min of end-exercise, Tmu10 reached resting values following approximately 40 min of recovery. These results suggest that during isolated muscle activity, convective heat transfer by the blood to non-active muscle tissue may have a significant role in maintaining resting core temperature.
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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) | 0.001 | 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".