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Record W2955286430 · doi:10.1080/08927936.2019.1621524

Does Viewing a Picture of a Pet During a Mental Arithmetic Task Lower Stress Levels?

2019· article· en· W2955286430 on OpenAlex
Natalie Ein, M. Said Al Hadad, Maureen J. Reed, Kristin S. Vickers

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnthrozoös · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStressorPsychologyTask (project management)Mental arithmeticStress (linguistics)Cognitive psychologySocial psychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Pets can reduce stress in their owner; however, they are not always permitted in public and institutional places. This study examined the impact of people viewing a picture of their pet versus other images on stress levels. One hundred and twenty participants were randomly assigned to one of six conditions. These involved completing a mental arithmetic task while viewing a picture of either their personal pet; an unfamiliar animal; a familiar, supportive person; a stranger; a pleasant image of nature; or no image. Stress was measured through subjective and physiological methods. For participants, viewing a picture of their pet did not reduce their stress response to the task, while viewing a picture of a familiar, supportive person increased the stress response, relative to the controls. Post-stressor, participants in the personal-pet condition rated the picture as making them feel more relaxed, compared with the other conditions. Active interaction with a pet may be required to reduce stress.

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.

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 score0.039
Threshold uncertainty score0.435

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 head0.011
GPT teacher head0.314
Teacher spread0.303 · 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