Bibliographic record
Abstract
Fatigue and potentiation are two forms of force modulation. A general definition of fatigue is "a circumstance where less than the anticipated contractile response is obtained." Fatigue is associated with depressed Ca2+ release and possibly decreased Ca2+ sensitivity. Potentiation results from increased Ca2+ sensitivity due to regulatory light chain phosphorylation. Muscle fatigue and potentiation can coexist, making it difficult to quantify these processes. With repetitive 10Hz stimulation, the developed tension first increases, then decreases. Is fatigue present when developed tension first begins to decrease or when it falls below the developed tension of the first response? Intermittent incompletely fused tetanic contractions for which peak developed tension first decreases, then increases, is another unusual example of fatigue. A third example is when twitch contractions following a tetanic contraction decrease to a level below the pretetanic twitch amplitude, indicating that fatigue may have been coexistent with posttetanic potentiation. These observations illustrate the complexity of detecting fatigue, based on the simple, but commonly accepted definition presented above. Care must be taken in interpreting "before vs. after" contractile responses. Even when the contraction amplitude is greater than the initial response, there is no guarantee that mechanisms associated with fatigue are not present.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".