Lyme borreliosis in Canada: biological diversity and diagnostic complexity from an entomological perspective
Bibliographic record
Abstract
Abstract Lyme borreliosis (LB), also known as Lyme disease, is emerging as a serious tickborne illness across Canada. More than three decades of research on LB in North America and Europe have provided a large, complex body of research involving well-documented difficulties at several levels. However, entomologists are well situated to contribute to resolving some of these challenges. The central pathogen in LB, the spirocheteBorrelia burgdorferiJohnsonet al., includes numerous genospecies and strains that are associated with different disease symptoms and distributions. The primary vectors of LB are ticks of variousIxodesLatreille species (Acari: Ixodida: Ixodidae), but questions linger concerning the status of a number of other arthropods that may be infected withB. burgdorferibut do not transmit it biologically. A variety of vertebrates may serve as reservoirs for LB, but differences in their ability to transmit LB are not well understood at the community level. Persistent cystic forms of and immune system evasion byB. burgdorfericontribute to extraordinary challenges in diagnosing LB. Multiple trade-offs constrain the effectiveness of assays like ELISA, Western blot, polymerase chain reaction, and microscopic visualization of the spirochetes. Consequently, opportunities abound for entomologists to contribute to documenting the diversity of the players and their interactions in this devilishly complex disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".