Structural modeling of contrast sensitivity in adulthood
Bibliographic record
Abstract
Structural equation modeling was used to assess the utility of the sensorineural model of contrast sensitivity proposed by Sekuler et al. [Vision Res. 24, 689 (1984)] to account for spatial vision in adulthood. In Study 1, visual acuity and contrast sensitivity (1.5-18 c/deg) were measured in 84 people between the ages of 19 and 81 yr. No three-filter model fitted the data well. Although a two-filter model was associated with good fit indices, parameter estimates for both filters were inconsistent with physiological and behavioral data. In Study 2, acuity and contrast sensitivity (1.5-18 c/deg) were assessed in 95 observers between the ages of 23 and 73 yr. All measures were gathered once per month over a three-month period. The Sekuler et al. three-filter model did not fit the data from any time of measure, but a two-filter, bandpass model provided a consistent and excellent fit for all three waves. The model suggests that age-related change in the neural mechanisms underlying contrast sensitivity is minimal once acuity is controlled. Discrepancies between this conclusion and that reported by Sekuler et al. may be related to test type, psychophysical method, reliability, and sample selection.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".