Cervico-Ocular and Vestibulo-Ocular Reflexes in Subclinical Neck Pain and Healthy Individuals: A Cross-Sectional Study
Bibliographic record
Abstract
Alterations in neck sensory input from recurrent neck pain (known as subclinical neck pain (SCNP)) result in disordered sensorimotor integration (SMI). The cervico-ocular (COR) and vestibulo-ocular (VOR) reflexes involve various neural substrates but are coordinated by the cerebellum and reliant upon proprioceptive feedback. Given that proprioception and cerebellar processing are impaired in SCNP, we sought to determine if COR or VOR gain is also altered. COR and VOR were assessed using an eye-tracking device in 20 SCNP (9 M and 11 F; 21.8 (SD = 2.35) years) and 17 control (7 M and 10 F; 22.40 (SD = 3.66) years) participants. COR gain (10 trials): A motorized chair rotated the trunk at a frequency of 0.04 Hz and an amplitude of 5° while participants gazed at a circular target that disappeared after three seconds. VOR gain (30 trials): Rapid bilateral head movements away from a disappearing circular target while eyes fixated on the last observed target. Independent t-tests on COR and VOR gain were performed. SCNP had a significantly larger COR gain (p = 0.006) and smaller VOR gain (p = 0.487) compared to healthy controls. The COR group differences suggest an association between proprioceptive feedback and SMI, indicating COR may be a sensitive marker of altered cerebellar processing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".