Manual action verbs modulate the grip force of each hand in unimanual or symmetrical bimanual tasks
Bibliographic record
Abstract
Manual action verbs modulate the right-hand grip force in right-handed subjects. However, to our knowledge, no studies demonstrate the ability to accomplish this modulation during bimanual tasks nor describe their effect on left-hand behavior in unimanual and bimanual tasks. Using load cells and word playlists, we evaluated the occurrence of grip force modulation by manual action verbs in unimanual and symmetrical bimanual tasks across the three auditory processing phases. We found a significant grip force increase for all conditions compared to baseline, indicating the occurrence of modulation. When compared to each other, the grip force variation from baseline for the three phases of both hands in the symmetrical bimanual task was not different from the right-hand in the unimanual task. The left-hand grip force showed a lower amplitude for auditory phases 1 and 2 when compared to the other conditions. The right-hand grip force modulation became significant from baseline at 220 ms after the word onset in the unimanual task. This moment occurred earlier for both hands in bimanual task (160 ms for the right-hand and 180 for the left-hand). It occurred later for the left-hand in unimanual task (320 ms). We discuss the hypothesis that Broca's area and Broca's homologue area likely control the left-hand modulation in a unilateral or a bilateral fashion. These results provide new evidence for understanding the linguistic function processing in both hemispheres.
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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 | 0.002 |
| 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) | 0.004 | 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".