Does a neuropsychological index of hemispheric lateralization predict onset of upper respiratory tract infectious symptoms?
Bibliographic record
Abstract
OBJECTIVES: Past studies demonstrate relationships between hemispheric lateralization (HL) and immunity. However, the relevance of HL-immune relationships to health and illness has rarely been investigated. This study tested whether a neuropsychological index of right-hemispheric lateralization (right-HL) predicts development of upper respiratory tract infectious (URTI) symptoms. DESIGN: We used a prospective, matched, case-control design. METHODS: Initially, 80 URTI symptom free adults underwent neuropsychological assessment including right-HL (picture vs. word recognition), and were then followed-up during 10 weeks for development of URTI symptoms and objective signs of URTI. Participants reporting URTI symptoms (Ill; N=21) were matched on age, gender, and IQ with 21 participants remaining well. RESULTS: At baseline, the right-HL index was significantly higher in participants who later became ill (9.9%) compared to well participants (3.9%, p<.05). Health behaviour also predicted URTI symptoms. In a logistic regression, right-HL significantly predicted self-reported URTI, independent of health behaviour and neuroticism. CONCLUSIONS: Greater right-HL predicted URTI symptom development during follow-up, independent of important confounders. These findings expand previous HL-immune relationships to a common immune-related illness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".