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Record W2300534960 · doi:10.1037/a0040009

Effects of aging on identifying emotions conveyed by point-light walkers.

2016· article· en· W2300534960 on OpenAlexafffund
J. Spencer, Allison B. Sekuler, Patrick Bennett, Martin A. Giese, Karin S. Pilz

Bibliographic record

VenuePsychology and Aging · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsMcMaster University
FundersBiotechnology and Biological Sciences Research CouncilCanadian Institutes of Health ResearchFP7 Information and Communication TechnologiesBundesministerium für Bildung und Forschung
KeywordsPsychologyBiological motionMotion (physics)Point (geometry)Age groupsDevelopmental psychologyCognitive psychologyCommunicationPerceptionComputer visionNeuroscience

Abstract

fetched live from OpenAlex

The visual system is able to recognize human motion simply from point lights attached to the major joints of an actor. Moreover, it has been shown that younger adults are able to recognize emotions from such dynamic point-light displays. Previous research has suggested that the ability to perceive emotional stimuli changes with age. For example, it has been shown that older adults are impaired in recognizing emotional expressions from static faces. In addition, it has been shown that older adults have difficulties perceiving visual motion, which might be helpful to recognize emotions from point-light displays. In the current study, 4 experiments were completed in which older and younger adults were asked to identify 3 emotions (happy, sad, and angry) displayed by 4 types of point-light walkers: upright and inverted normal walkers, which contained both local motion and global form information; upright scrambled walkers, which contained only local motion information; and upright random-position walkers, which contained only global form information. Overall, emotion discrimination accuracy was lower in older participants compared with younger participants, specifically when identifying sad and angry point-light walkers. In addition, observers in both age groups were able to recognize emotions from all types of point-light walkers, suggesting that both older and younger adults are able to recognize emotions from point-light walkers on the basis of local motion or global form.

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 score0.033
Threshold uncertainty score0.307

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 head0.014
GPT teacher head0.357
Teacher spread0.343 · 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

Citations37
Published2016
Admission routes2
Has abstractyes

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