The Open Perimetry Interface: An enabling tool for clinical visual psychophysics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perimeters are commercially available instruments for measuring various attributes of the visual field in a clinical setting. They have several advantages over traditional lab-based systems for conducting vision experiments, including built-in gaze tracking and calibration, polished appearance, and attributes to increase participant comfort. Prior to this work, there was no standard to control such instruments, making it difficult and time consuming to use them for novel psychophysical experiments. This paper introduces the Open Perimetry Interface (OPI), a standard set of functions that can be used to control perimeters. Currently the standard is partially implemented in the open-source programming language R on two commercially available instruments: the Octopus 900 (a projection-based bowl perimeter produced by Haag-Streit, Switzerland) and the Heidelberg Edge Perimeter (a CRT-based system produced by Heidelberg Engineering, Germany), allowing these instruments to be used as a platform for psychophysical experimentation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it