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Record W4386316903 · doi:10.1002/9781119862611.ch22

Communicating with Pet Parents

2023· other· en· W4386316903 on OpenAlexaff
Robin Saar, Sarah Dodd

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsVariety (cybernetics)PsychologyAction (physics)Process (computing)Plan (archaeology)Social psychologyApplied psychologyComputer science

Abstract

fetched live from OpenAlex

Pet parents want to be included in the decision-making process concerning their pets' health and treatment plan, though a variety of factors may preclude them from being able to follow veterinarian recommendations. Creating trust between pet parents is the main component when developing a veterinarian–client–patient relationship (VCPR). It includes aiding the pet parents in making decisions about their pets' health, and it may be one of the most complex and difficult components of the VCPR relationship. The protection motivation theory (PMT) describes how individuals are motivated to react in a self-protective way toward a perceived threat. Changing behavior can be difficult and requires ongoing support to ensure the illicit of new behaviors. Self-affirmation is identifying and communicating an important or positive aspect about the pet parent before giving information that may be perceived as negative. Action plans should be clear and provide well-explained guidance for the steps a pet parent should follow.

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)0.003
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0630.013

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 head0.362
Teacher spread0.333 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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Same topicHuman-Animal Interaction StudiesFrench-language works237,207