Comparing Apples and Oranges
Bibliographic record
Abstract
The interpolated twitch technique (ITT) is a widely used method to assess voluntary activation (VA) in humans while performing a maximal voluntary contraction (MVC). The technique involves a superimposed twitch (SIT) evoked via electrical activation of the motor nerve or direct muscle stimulation during the MVC, and a control twitch (CT) evoked up to 3s following relaxation. By comparing SIT to CT, VA can be quantified. However, the SIT and CT are evoked over different fascicle lengths (Lf) which may cause inappropriate estimation of VA. The SIT is evoked while the muscle is contracting and presumably at a shorter Lf than that reached during the CT. Therefore, the SIT and CT are evoked on different portions of the force-fascicle length (F-Lf) relationship thereby potentially misrepresenting VA. PURPOSE: To investigate the assessment of VA using the ITT during electrically evoked tetanic contractions in the rat and observe systematically, using sonomicrometry, differences in the F-Lf relationship conditions in which the SIT and CT are evoked. METHODS: Sprague Dawley rats were anaesthetized, the medial gastrocnemius (MG) was surgically isolated and tied in series with a length controller and force transducer. An individual muscle fascicle was identified by direct electrical stimulation. Sonomicrometry crystals were implanted at the distal and proximal ends to measure ΔLf. The sciatic nerve was carefully dissected, placed in a nerve cuff and all nerve branches to muscles other than the MG were cut. Six experimental conditions were performed: tetanic contractions at 200Hz stimulation and an evoked SIT and CT were performed at short, optimal, and long muscle lengths at a submaximal and maximal force level. RESULTS: The SIT Lf was evoked near optimal Lf the CT was evoked at longer Lf corresponding to less than optimal force. This suggests an underestimation of VA at long lengths and overestimation of VA at short lengths. CONCLUSION: As expected the SIT and CT were evoked at different Lf and therefore on different portions of the F-Lf relationship. These results suggest VA may be misrepresented as a result of differences in Lf at which the twitches are evoked. The magnitude of this error depends on actual in-series compliance. Caution must be taken when interpreting the VA results. Supported by: NSERC and CIHR
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".