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Record W4304957943 · doi:10.5864/d2022-018

The role of climate change in the spread of vectors and vector-borne disease in Windsor-Essex County

2022· article· en· W4304957943 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Health Review · 2022
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsConestoga College
Fundersnot available
KeywordsWindsorClimate changeVector (molecular biology)Public healthGeographyEcologyBiologyMedicine

Abstract

fetched live from OpenAlex

West Nile virus (WNV) and Lyme disease have emerged as significant public health concerns in many parts of Canada. Vector-borne diseases (VBDs) are susceptible to climate change and changing weather patterns because mosquitoes’ and ticks’ lifecycles are significantly impacted by temperature, precipitation, and humidity. Over the last several decades, weather patterns related to climate change in Windsor-Essex County demonstrate tendencies for the further proliferation of invasive mosquito species in the area. In this study, increasing maximum January and February temperatures and number of days in May with temperatures above 30 °C demonstrated a positive impact on the number of WNV-positive pools and the annual rate of WNV. Given the results of this study, health units should consider adapting their vector-borne management strategies and risk assessment tools to include these parameters, which can help health units assess VBD risks for people during the season and develop risk communication strategies to protect public health.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.367
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.291
Teacher spread0.279 · 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