Target range properties do not influence oculomotor undershooting bias.
Bibliographic record
Abstract
An exemplar property of goal-directed saccades is the undershooting of veridical target location: a property that has been tied to an energy minimizing bias that reduces the physiological and psychological costs of target overshooting. Interestingly, however, Kapoula (1985) reported that task properties and the range of target eccentricities presented within discrete trial blocks engenders a saccade overshooting bias (so-called range effect). In the present investigation, we sought to determine whether the range of target eccentricities associated with serially presented blocks modulates saccade endpoint bias. To that end, participants (N=20) completed saccades to briefly (i.e., 50 ms) presented targets in two separate blocks. The first block employed a "small" range of target eccentricities (i.e., 3, 5.5, 8, 10.5, and 13[sup]o[/sup]), whereas the second block entailed a "large" range of eccentricities (i.e., 10.5, 13, 15.5, 18, and 20.5[sup]o[/sup]). Notably, the ordering of blocks was constant and two common eccentricities were associated with each (i.e., 10.5 and 13[sup]o[/sup]). Thus, if a range effect influences goal-directed saccades then the undershooting bias associated with the 10.5[sup]o[/sup] and 13[sup]o[/sup] targets in the first block should exhibit an overshooting bias in the second block. Results for saccade amplitude revealed a reliable undershooting of all target eccentricities in both blocks. Moreover, a between-block comparison of the congruent target eccentricities (i.e., 10.5[sup]o[/sup] and 13[sup]o[/sup]) yielded an equivalent undershooting bias. Therefore, results provide no evidence to support a range effect in oculomotor control. Instead, the results are consistent with models of energy minimization and the assertion that oculomotor responses are designed to minimize movement time and energy expenditure. This study was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). Meeting abstract presented at VSS 2013
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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 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".