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Record W2050086338 · doi:10.7589/0090-3558-37.4.730

ACCEPTANCE OF BAITS FOR DELIVERY OF ORAL RABIES VACCINE TO RACCOONS

2001· article· en· W2050086338 on OpenAlexaffabout
Richard C. Rosatte, K F Lawson

Bibliographic record

VenueJournal of Wildlife Diseases · 2001
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsTrent UniversityMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsRabiesBiologyVirologyVeterinary medicineZoologyMedicine

Abstract

fetched live from OpenAlex

During 1993-96 the Ontario Ministry of Natural Resources (Canada) implemented a research project to evaluate the efficacy of three candidate baits to deliver oral rabies vaccine to wild raccoons (Procyon lotor). Extensive field testing revealed that raccoon acceptance of Sugar-Vanilla baits (SV) at densities of 200/km2 and 400/km2, hand-placed in urban habitats of Scarborough (Ontario) during 1993, was 74% and 82%, respectively. Raccoon density in those areas averaged 11/km2. Aerial placement of SV baits in rural habitats in Barrie (Ontario) during 1993 and 1994, yielded raccoon acceptance levels of 58% with a density of 100 baits/km2, 59% at 75 baits/km2, and 47% at 50 baits/km2. Raccoon acceptance of SV baits was significantly lower in areas baited at the density of 50/km2. Acceptance of Cheese baits (CH) at a density of 75 baits/km2 was 52%. During 1996 trials in Barrie, modified SV baits with blister packs protruding through the matrix yielded raccoon acceptance values of 51% at a bait density of 54/km2, whereas acceptance of regular SV baits was 39% at a density of 51 baits/km2. Pooling of bait acceptance data for all years revealed that bait acceptance was highest for adult male raccoons. Raccoon density in rural habitats (Barrie, Ontario) where the studies took place, averaged 11-13/km2. Puncture and impact testing of blister packs in baits suggested that they would adequately serve as a vehicle to contain oral rabies vaccine for delivery to raccoons via baits.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.281
Teacher spread0.265 · 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.

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

Citations27
Published2001
Admission routes2
Has abstractyes

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