A Compact Clinical Instrument for Quantifying Suppression
Bibliographic record
Abstract
PURPOSE: We describe a compact and convenient clinical apparatus for the measurement of suppression based on a previously reported laboratory-based approach. In addition, we report and validate a novel, rapid psychophysical method for measuring suppression using this apparatus, which makes the technique more applicable to clinical practice. METHODS: By using a Z800 dual pro head-mounted display driven by a MAC laptop, we provide dichoptic stimulation. Global motion stimuli composed of arrays of moving dots are presented to each eye. One set of dots move in a coherent direction (termed signal) whereas another set of dots move in a random direction (termed noise). To quantify performance, we measure the signal/noise ratio corresponding to a direction-discrimination threshold. Suppression is quantified by assessing the extent to which it matters which eye sees the signal and which eye sees the noise. RESULTS: A space-saving, head-mounted display using current video technology offers an ideal solution for clinical practice. In addition, our optimized psychophysical method provided results that were in agreement with those produced using the original technique. We made measures of suppression on a group of nine adult amblyopic participants using this apparatus with both the original and new psychophysical paradigms. All participants had measurable suppression ranging from mild to severe. The two different psychophysical methods gave a strong correlation for the strength of suppression (rho = -0.83, p = 0.006). CONCLUSION: Combining the new apparatus and new psychophysical method creates a convenient and rapid technique for parametric measurement of interocular suppression. In addition, this apparatus constitutes the ideal platform for suppressors to combine information between their eyes in a similar way to binocularly normal people. This provides a convenient way for clinicians to implement the newly proposed binocular treatment of amblyopia that is based on antisuppression training.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".