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Record W2523269098

RECRUITMENT OF WINTER TICKS (DERMACENTOR ALBIPICTUS) IN CONTRASTING FOREST HABITATS, ONTARIO, CANADA

2016· article· en· W2523269098 on OpenAlexaffabout
Edward M. Addison, Robert F. McLaughlin, Peter A. Addison, Johan Smith

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsCentre de Recherche en Sciences Animales de DeschambaultMinistry of ForestsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsHabitatEcologyDermacentorGeographyTickForestryBiologyIxodidae
DOInot available

Abstract

fetched live from OpenAlex

Recruitment of winter tick larvae (Dermacentor albipictus) was studied in a forest opening and a closed canopy deciduous forest to evaluate their potential as sources of tick infestation to moose (Alces alces). Engorged female ticks were set out in early May at each site and monitored to measure the proportions of females producing larvae and the number of larvae recruited per g of surviving female. Recruitment was higher in the forest during the hotter, drier summer of 1983, primarily due to fewer engorged females producing larvae in the opening, and was much higher (>2 x) in the opening during the cooler, damper summer of 1984. Recruitment in the field was 20–40% of that under laboratory conditions. Desiccation of eggs and/or larvae was the probable cause for the annual variation in recruitment in the opening. Most larvae were recruited earlier in the opening than in the forest site. Neither weight nor date of detachment of engorged female ticks influenced when larvae first ascended vegetation. Weather, especially temperature, and site structure and composition affect abundance of the free-living stages of the winter tick and larvae available for transmission to moose. Open sites should support more winter tick larvae than densely forested sites except in years of particularly hot and dry weather.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.000

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 head0.160
GPT teacher head0.461
Teacher spread0.301 · 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 teacher head, not a consensus.

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

Citations9
Published2016
Admission routes2
Has abstractyes

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Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicVector-borne infectious diseasesFrench-language works237,207