Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Muscle synergies have been proposed as building blocks that could simplify the construction of motor behaviors. However, the muscles within synergistic groups may have different architectures, mechanical linkages to the skeleton, and biochemical properties, and these put competing demands on the most appropriate way to activate them for different mechanical tasks. This study identifies the extent to which synergistic patterns of muscle activity vary when the mechanical demands on a limb were altered, and additionally identifies how consistent the spectral profiles of the electromyographic (EMG) intensities were across the different movement tasks. The muscle activities were measured with surface EMG across 10 muscles in the leg during cycling at a range of loads and velocities. The EMGs were quantified by their intensities in time-frequency space using wavelet analysis; the instantaneous patterns of activity identified using principal component analysis, statistically compared and further visualized using the varimax rotation. Variability (35.7%) in the patterns of activity between the muscles were correlated with the torque and velocity of the pedal crank. Anatomic groups of muscles share a common mechanical action across a joint; uncoupling between such muscles was identified in 68.8% of the varimax patterns that encompassed all 10 muscles and 20.8-29.5% of the activity patterns when the anatomic groups were analyzed separately. The EMG spectra showed greatest heterogeneity for the gastrocnemii. These results show that the activity of muscles within anatomic groups is partially uncoupled in response to altered mechanical demands on the limb.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it