Global Motion: effects of spatial scale and eccentricity
Bibliographic record
Abstract
Purpose. Much is known about global motion processing, the ability to extract the global motion attributes from a collection of noisy local motion signals. Less is known about its dependence on spatial scale and eccentricity because it has been general practice to use large fields of spatially broadband stimuli. Here we first look at the effects of spatial scale and, equipped with this knowledge, explore the dependence on eccentricity. Methods Our stimulus comprised an array of spatially bandpass elements in which some of the elements (signal) move in a coherent direction while the other elements (noise) move in a random direction. We vary the contrast of the individual elements and measure, using a standard 2AFC task, the signal/noise threshold (coherence) for motion direction.Results The detectability of the elements is strongly spatial scale dependent as is the influence of eccentricity, however coherence thresholds are, to a large extent, independent of both spatial scale and eccentricity. Conclusion The effects of spatial scale and eccentricity being strongly contrast dependent reflect the low-level dependencies of local motion processing. At the level where global integration occurs such factors exert only small effects.
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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) | 0.002 | 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".