MétaCan
Menu
Back to cohort
Record W4414689148 · doi:10.1080/00221325.2025.2564992

COVID-19 and Protective Equipment: Impact of the Obstruction of Facial Features on the Recognition of Emotional Facial Expressions in Children

2025· article· en· W4414689148 on OpenAlexafffund
Mylène Michaud, Mélanie Perron, Adèle Gallant, Anne-Marie Rainville, Annie Roy‐Charland

Bibliographic record

VenueThe Journal of Genetic Psychology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversité LavalLaurentian UniversityUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDisgustFacial expressionSurpriseHappinessEmotional expressionSadnessFace (sociological concept)Facial Action Coding System

Abstract

fetched live from OpenAlex

The arrival of COVID-19 came along with the requirement of wearing protective gear, like facial masks, which potentially affects the recognition of facial expressions in others. The aim of the current study was to examine the impact of a facial feature obstruction on emotional facial expression recognition of the six basic emotions in children aged 5 and 10 years old. Children were presented 24 stimuli within two different conditions: the full face and only the eyes visible. While both age groups were similarly affected by reduced facial information, differences emerged depending on the emotion: 5-year-olds struggled more with recognizing happiness from just the eyes, whereas 10-year-olds had more difficulty with anger. Nevertheless, both age groups had a significant reduction in accuracy for most emotions (4 out 6). Common confusions, such as mistaking fear for surprise or disgust for anger, might have contributed to the variations in results from previous studies.

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)0.001
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 score0.937
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.055
GPT teacher head0.368
Teacher spread0.312 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Genetic PsychologySame topicFace Recognition and PerceptionFrench-language works237,207