Facilitating the Use of Online Visual Feedback: Advance Information and the Inter-Trial Interval?
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
Cheng et al. (2008) showed that when goal-directed reaching movements are performed with a 2.5 s inter-trial interval (ITI) under a randomized visual feedback schedule, individuals use online visual information on trial n to perform efficient online corrections on trial n + 1 (i.e., "reminiscence" effect). These results persisted even when participants were given knowledge of the up-coming vision condition. In this study, the ITI was extended to 5 s in an attempt to negate any effects of the preceding trial. Results from this study revealed that trials with vision were always more accurate than trials performed without vision, suggesting that individuals relied significantly on online information. Furthermore, aiming precision improved when participants knew the vision condition before each trial. It is thus suggested that the reminiscence effects are not longer evident with a 5 s ITI, which in turn allows prior knowledge of visual feedback to influence the use of online vision.
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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 | 0.004 |
| 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 | 0.001 |
| 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