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Record W4307122580 · doi:10.3390/ani12212897

Beyond “Doing Better”: Ordinal Rating Scales to Monitor Behavioural Indicators of Well-Being in Cats

2022· article· en· W4307122580 on OpenAlexaff
Jacklyn J. Ellis

Bibliographic record

VenueAnimals · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsWildlife Conservation Society Canada
Fundersnot available
KeywordsReliability (semiconductor)Psychological interventionRating scalePsychologySafeguardingApplied psychologyAnxietyScale (ratio)Interclass correlationComputer scienceStatisticsIntraclass correlationClinical psychologyDevelopmental psychologyPsychometricsMedicineMathematicsGeography

Abstract

fetched live from OpenAlex

Safeguarding the well-being of cats is essential to the mission of any responsible animal shelter. Environmental enrichment and behaviour modification are often key to this goal. Measuring response to these interventions is essential to ensure strategies are successful. There are often many staff and volunteers involved in these efforts, and a lack of standardised language can make monitoring progress difficult. Ordinal rating scales of key behaviours can be a useful way to summarise observations and ensure that common language is used. However, it is crucial that these scales have good interobserver agreement and reliability, so operational definitions and training systems are important. This paper presents a method for evaluating four different expressions of cat welfare on a 0-5 scale: modified Fear, Anxiety, and Stress score; Response to Petting score; Participation in Play score; and Food Intake Summary score. All scales showed almost perfect average interobserver agreement (linear weighted κ) and excellent average interobserver reliability (interclass correlation coefficient). These scales may prove useful to other shelters, or any other environment where evaluating response to interventions is important to the welfare of cats, such as research facilities or home environments. The exceptional interobserver agreement and reliability of this study compared with some others highlights the importance of standardised training programs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.321
Teacher spread0.309 · 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 designBench or experimental
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

Citations15
Published2022
Admission routes1
Has abstractyes

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