Cause of asymmetries in center-surround and surround-center masking
Bibliographic record
Abstract
Olzak, Gabree, Saarela, and Laurinen (under review) performed center-surround masking experiments with suprathreshold sinusoidal gratings, and observed asymmetries in masking. When making judgments on the center component they showed that adding an abutting annulus (surround) mask decreased performance relative to a control task. However, when judgments were based on the surround, an abutting center mask had no effect on performance. Eye tracking experiments, using identical stimuli, indicated different locations of fixation for the two different judgments (center or surround). When making judgments on the surround observers fixated around the outer perimeter of the annulus, where as when making judgments on the center observers fixated on locations much more central to the stimulus. This different pattern in the results may be caused by a difference in the organization of the mask and test components. When performing discrimination tasks on the center the test stimulus is masked on all sides. Conversely, when performing discrimination tasks on the surround, the test stimulus is masked on only one side. To test whether the organization of components affected performance we conducted a masking experiment with rectangular sinusoidal stimuli. The test stimulus was a rectangular sinusoid masked on one side (top, bottom, left or right) by a constant abutting grating of the same size. This organization closely replicates the possible conditions under which surround judgments were made. In all participants, masking still occurred irrespective of the location of the abutting grating. These results indicate that the asymmetries that have previously been reported are not due to mask-stimulus organization, but may be due to the segmentation of components into independent objects.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".