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Record W2260244617

Ontario Equine Infectious Disease Report now available to equine practitioners throughout Canada.

2003· letter· en· W2260244617 on OpenAlexaboutno aff
Hutchison Ja

Bibliographic record

VenuePubMed · 2003
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsInfectious disease (medical specialty)MedicineChristian ministryDiseaseDisease surveillanceFamily medicinePolitical sciencePathology
DOInot available

Abstract

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Dear Sir, The Ontario Ministry of Agriculture and Food, the University of Guelph Animal Health Laboratory, and the Ontario Veterinary College have recently established an informal network to improve communication on issues involving equine infectious disease and to streamline disease reporting. One aspect of this collaboration is the publication of a quarterly newsletter, the Ontario Equine Infectious Disease Report. The objectives of this newsletter are to inform veterinarians about emerging issues involving infectious disease and to provide general information on infectious disease. The upcoming edition has information on West Nile virus (WNV) surveillance and Eastern equine encephalomyelitis in Ontario, deworming programs, viral respiratory tract disease surveillance, WNV vaccine safety, intravenous WNV antibody treatment, and mare reproductive loss syndrome. The newsletter is available only in electronic format and is distributed via e-mail to members of the Ontario Association of Equine Practitioners via their list-server. While the newsletter is based on disease issues in Ontario, most of the information would be relevant to veterinarians involved in equine practice throughout Canada. To promote broader circulation, the newsletter will now be made available electronically to any veterinarian or veterinary group. Veterinarians wishing to be included in the electronic mailing should send an e-mail to Scott Weese (ac.hpleugou@eseewsj).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.205
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.212
Teacher spread0.183 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2003
Admission routes1
Has abstractyes

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