Diltiazem-induced Vertical Eye-movement Hypometria Detected By A High-speed Eye Tracking System Optimized For Clinical Investigation
Bibliographic record
Abstract
This paper discusses the optimization of a high-speed (1 kHz) 1st-Purkinje eye-tracking system for use in a clinical research setting. Through the use of stimulus generation and data analysis software, saccadic, pursuit, and fixation eye movements can be easily elicited, recorded, and analyzed in a clinical population. The system was used to investigate the effects of the L-type (slow) calcium channel blocker diltiazem on oculomotor performance in a single subject. Vertical saccades were found to have a significant decrease in accuracy (undershoot) (p < 0.05, one-way ANOVA). Increased variance was observed for gain and phase responses of pursuit movements. No significant changes were observed in central or lo eccentric fixations. L-type calcium channels are found in high numbers (50-100-fold higher than in cardiac membranes) in skeletal muscle t-tubules, including those in extraocular muscle. We have shown the use of diltiazem to be associated, with a previously-unreported vertical eye movement hypometria.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".