Protocol for a longitudinal cohort study of Lyme disease with physical, mental and immunological assessment
Bibliographic record
Abstract
INTRODUCTION: There are limited data on the longitudinal impact of Lyme disease. Predictors of recovery have not been fully established using validated data collection instruments. There are sparse data on the immunological response to infection over time. METHODS AND ANALYSIS: This study is a longitudinal cohort study that will recruit 120 participants with Lyme disease in Ontario and Nova Scotia, Canada, with follow-up for up to 24 months. Data will be collected using the Short-Form 36 physical and mental component summaries, Depression and Anxiety Severity Scale Questionnaire, Fatigue Severity Scale and a battery of neuropsychological tests. Mononuclear cells, gene expression and cytokine profiling from blood samples will be used to assess immunological response. Analyses will include the use of non-linear mixed-effects modelling and proportional hazards models. ETHICS AND DISSEMINATION: Ethics approval has been obtained from ethics boards at McMaster University (Hamilton Integrated Research Ethics Board) (7564), Queens University (EMD 315-20) and Nova Scotia Health Research Ethics Board (1027173), and the study is enrolling participants. Written informed consent is obtained from all participants. The results will be disseminated by publication in a peer-reviewed journal and presented at a relevant conference. A brief report will be provided to decision-makers and patient groups.
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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 | 0.045 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.074 | 0.018 |
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".