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Record W4401901027 · doi:10.56771/jsmcah.v3.91

Online Training Using an Educational Video Improves Human Ability To Identify and Rate Kitten Fear Behavior

2024· article· en· W4401901027 on OpenAlexaff
Courtney Graham, S. Hurley, David L. Pearl, Georgia Mason, Lee Niel

Bibliographic record

VenueJournal of Shelter Medicine and Community Animal Health · 2024
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsKittenTraining (meteorology)PsychologyComputer scienceApplied psychologyMultimediaCATSGeography

Abstract

fetched live from OpenAlex

Introduction: Fear is a negative emotional state that can influence early behavioral development and lead to impairments in animal welfare. For young kittens, excessive fear early in life can instill lasting fearfulness leading to behavioral issues such as aggression, negative impacts on the human–animal bond, potential mistreatment, relinquishment to shelters, and/or euthanasia. Therefore, it is crucial that caretakers can accurately identify when their kittens might be experiencing fear in order to respond appropriately. Methods: We used an online survey to determine: (1) whether members of the general public (n = 761) can accurately identify and rate different severities of fear behavior in young kittens in short video clips (i.e. no fear requiring no intervention, mild fear requiring awareness of possible intervention, and moderate fear requiring immediate intervention); and (2) whether an educational video offering specialized training on identifying kitten behavior can improve human ability to correctly rate kitten behavior in comparison to a general kitten care video. Results: Using mixed logistic regression models, we found no difference at baseline in correct ratings between the two video groups across all fear categories. However, participants who received the specialized behavior training had significantly greater odds of being correct after video training for all three categories compared to participants who received the general kitten care video. Additionally, previous experience with cats and participant personality impacted ratings. Conclusions: Overall, the current study demonstrates that concise and specialized training in identifying kitten behavior is a useful tool for improving human ability to identify and rate fear levels in kittens. This training approach can help strengthen caretaker understanding of kitten behavior to ensure interactions with potentially fear-provoking stimuli are properly mitigated to reduce related welfare impacts. Thus, these types of educational resources are encouraged within shelters, veterinary clinics, research settings, and foster and adoptive homes to improve the welfare of kittens.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.298
GPT teacher head0.513
Teacher spread0.215 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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