Discrimination of amplitude spectrum slope in the fovea and parafovea and the local amplitude distributions of natural scene imagery
Bibliographic record
Abstract
A number of studies have investigated whether human visual performance can be related to the general form of the amplitude spectra (i.e., 1/f(alpha)) of natural scenes. Here, it is argued that there are some discrepancies in the data between some of those studies and that one possible explanation for the discrepancies may be related to differences in methodology (e.g., stimuli presented to the fovea as opposed to the parafovea). We sought to resolve some of the discrepancies with two psychophysical paradigms involving alpha discrimination with visual noise and natural scene image patches presented to the fovea or parafovea. Fovea-parafovea threshold differences were apparent for stimuli possessing alpha values < 1.0, with the parafovea typically showing highest thresholds for reference alpha values in the 0.74-0.85 range. Both fovea and parafovea thresholds were lowest in the 1.2-1.4 range. In addition, we conducted a local amplitude distribution analysis (i.e., assessed local alpha) with a large set of high-resolution natural scene imagery and found that the results of that analysis provided a better account of the alpha discrimination thresholds for stimuli presented to the fovea as opposed to the parafovea.
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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 | 0.001 | 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 | 0.000 |
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".