From discrete to continuous online limb-target regulation processes: A matter of time?
Bibliographic record
Abstract
A pseudo-continuous model of online sensorimotor control suggests that visual information is gathered from peak acceleration until movement end (Elliott et al., 2010). Although seminal evidence for the model employed relatively slow movements, Tremblay et al. (2013; 2017) have provided evidence for optimal online visual information utilization during early stages of fast reaching movements (i.e., ~350 ms). The current study examined the generalizability of these results to faster and slower reaching movements (i.e., 350 ms or 700 ms). During reaching movement participants were provided with a 20 ms window of visual information (i.e., at 35%, 60% or, 85% of PV) and a target-jump manipulation. Overall, the strategy to implement a single correction was supported for faster movements, whereas the pseudo-continuous model (Elliott et al., 2010) was supported for slower movements. Theoretically, online visual uptake strategies could be merely dependent on the time available for utilization and implementation of amendments.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.015 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".