Characteristics of Human Corneal Psychophysical Channels
Bibliographic record
Abstract
PURPOSE: To characterize human corneal psychophysical channels. METHODS: Twenty subjects participated in this study. A Belmonte pneumatic esthesiometer was used to deliver stimuli, and the ascending method of limits and the method of constant stimuli were used to estimate thresholds. Sensation was characterized for different stimuli. Corneal mechanical and chemical thresholds were measured at different temperatures. RESULTS: The qualities of the sensations induced by stimuli with different temperatures were different, and the corresponding detection thresholds of the pneumatic stimuli at four temperatures gradually increased (repeated measures ANOVA (F(3,12) = 10.326, P = 0.000). There were no temperature effects on chemical thresholds (repeated measures ANOVA F(3,12) = 0.235, P = 0.870) or mechanical discomfort thresholds from 20 degrees C to 50 degrees C (paired t14 = -0.233, P = 0.818). There were strong interactions when chemical and mechanical stimuli were added. Chemical thresholds were progressively lower when the flow rate increased and mechanical thresholds went down as the percentage of added CO2 increased (repeated measures ANOVA F(3, 12) = 6.407, P = 0.007, F(4, 16) = 19.904, P = 0.000). CONCLUSIONS: This study suggests that humans sense corneal non-noxious cold and noxious mechanical and chemical stimuli, and that the sensitivity of some submodalities can be modulated by others. There are at least five psychophysical channels (non-noxious cold, noxious mechanical, noxious chemical-H+, noxious heat, and itching) processing corneal sensory information. Both decreased corneal chemical thresholds at high flow rates and decreased mechanical thresholds with an added chemical stimulation demonstrate that corneal psychophysical channels are not independent.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".