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Record W3160765250

Companion animal preventive care at a veterinary teaching hospital - Knowledge, attitudes, and practices of clients.

2021· article· en· W3160765250 on OpenAlexaffabout
Michelle Evason, M. A. McGrath, Jason W. Stull

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsMedicineFamily medicineCornerstoneVaccinationPreventive healthcareHealth carePreventive careDisease controlVeterinary medicineNursingPublic healthEnvironmental healthPathology
DOInot available

Abstract

fetched live from OpenAlex

Preventive care is the cornerstone of health. However, veterinary staff to client (pet owner) communication of disease prevention may be limited resulting in increased pet risk. Our objectives were to evaluate knowledge, attitudes, and practices of clients regarding vaccination and parasite control and describe information sources influencing client preventive care. Over a 6-week period, clients visiting a veterinary teaching hospital in Prince Edward Island, Canada, were invited to complete a written questionnaire. Of those invited, 81% (105/129) completed the questionnaire. Respondents reported low (19 to 33%) to moderate (66 to 79%) coverage for canine "lifestyle" and core vaccines, respectively. Half of the participants reported that they had concern for their pet's health from endo/ectoparasites compared to concern for their/household member's health (27%), despite 45% reporting a person at increased zoonotic risk in their household. Veterinarians (89 to 92%) and online information (39 to 51%) were the highest client-reported resources for vaccine and parasite education. Our work provides a baseline for preventive care practices and highlights a need for improvement.

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)0.004
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 score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.037
GPT teacher head0.351
Teacher spread0.314 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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