Bibliographic record
Abstract
The existence of a second-order motion system distinct from both the first-order and feature tracking motion systems remains controversial even though many consider it well established. In the present study, the texture contribution to motion was measured within and beyond the spatial acuity of attention by presenting the stimuli in the near periphery where the spatial resolution of attention is low. The logic was that when moving elements are too close one to another for attention to individually select them (i.e., crowding), it is not possible to track them. To test the existence of a dedicated second-order motion system, the texture contribution to motion was measured when neutralizing both the feature tracking motion system and the contribution of the first-order motion system due to preprocessing nonlinearities introducing residual distortion products. When the contribution of distortion products was not neutralized, texture substantially contributed to motion for spatial frequencies within and beyond the spatial acuity of attention. When neutralizing the contribution of distortion products, texture substantially contributed to motion for spatial frequencies within the spatial acuity of attention, but not for spatial frequencies beyond the spatial acuity of attention. We conclude that there is no dedicated second-order motion system; the texture contribution to motion is mediated solely by the first-order (due to residual distortion products) and feature tracking (at frequencies within spatiotemporal acuity of attention) motion systems.
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.
How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".