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Record W3111778853 · doi:10.3390/ani10122308

Beloved Whiskers: Management Type, Care Practices and Connections to Welfare in Domestic Cats

2020· article· en· W3111778853 on OpenAlexaff
Daiana de Souza Machado, Luana da Silva Gonçalves, Rogério Ribeiro Vicentini, Maria Camila Ceballos, Aline Cristina Sant’Anna

Bibliographic record

VenueAnimals · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsContingency tableWelfareDescriptive statisticsCategorical variableBusinessAnimal welfareTest (biology)Environmental healthPsychologyMedicineStatisticsMathematicsBiologyEcologyEconomics

Abstract

fetched live from OpenAlex

The quality of cat care practices depends in part on the type of management applied, which either positively or negatively impacts cat welfare. This study investigated whether the type of cat management (indoor vs. outdoor) was related to other cat care practices adopted by cat owners, associated with the quality of human-cat relationships and cat welfare. An online survey was distributed via social networks. Descriptive statistics, categorical Principal Component Analysis, Fisher's Exact test and Chi-square test in contingency table were applied. A total of 16,302 cat owners returned the survey. Most Brazilian owners reported indoor management of their cats; this was related to owners living in apartments, more frequent use of cat care practices, and more interactions with their pets. Outdoor management was related to cats living in houses or farms, sleeping outdoors or around the neighborhood, and owners had fewer interaction with their pets. In conclusion, owners practicing indoor management seemed to be closer to their cats than owners reporting outdoor management. However, obesity and owner-reported behavioral problems were associated with indoor management.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.408

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 head0.035
GPT teacher head0.381
Teacher spread0.346 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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