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Record W4402828374 · doi:10.3201/eid3010.240191

Age- and Sex-Specific Differences in Lyme Disease Health-Related Behaviors, Ontario, Canada, 2015–2022

2024· article· en· W4402828374 on OpenAlexaboutno aff
Janica Adams, Victoria Osasah, Katherine Paphitis, Affan Danish, Richard Mather, Curtis A. Russell, Jennifer Pritchard, Mark P. Nelder

Bibliographic record

VenueEmerging infectious diseases · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
Fundersnot available
KeywordsLyme diseaseMen who have sex with menMedicineDiseaseDemographyEnvironmental healthGerontologyVirologyInternal medicineSyphilisHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

We investigated differences in risk factors and preventive behaviors by age and sex among persons with reported Lyme disease in Ontario, Canada, during 2015-2022. Incidence rates peaked among children 5-9 and adults 50-79 years of age. Median age was higher for female than male case-patients (54 vs. 51 years). Male case-patients reported more activity in wooded and tall grass areas than did female case-patients; fewer male case-patients reported sharing living space with outdoor-exposed companion animals. As age increased, more case-patients reported activity in blacklegged tick habitats, exposure to ticks, and wearing adequate clothing, but fewer reported sharing living space with outdoor-exposed companion animals. Adoption of preventive behaviors was relatively low and did not differ by sex. Male case-patients, children 5-9 years of age and their parents or caregivers, and adults >59 years of age represent populations that would benefit from tailored public health messaging on Lyme disease prevention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.236
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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