MétaCan
Menu
Back to cohort
Record W1970235386 · doi:10.1167/11.3.4

Allocation of attention to biological motion: Local motion dominates global shape

2011· article· en· W1970235386 on OpenAlexafffund
Masahiro Hirai, Daniel R. Saunders, Nikolaus F. Troje

Bibliographic record

VenueJournal of Vision · 2011
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsQueen's University
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsBiological motionSaccadeLatency (audio)Computer visionMotion (physics)Computer scienceArtificial intelligenceTask (project management)Eye movementMovement (music)TelecommunicationsPhysicsEngineeringAcoustics

Abstract

fetched live from OpenAlex

Directional information can be retrieved from a point-light walker (PLW) in two different ways: either from recovering the global shape of the articulated body or from signals in the local motion of individual dots. Here, we introduce a voluntary eye movement task to assess how the direction of a centrally presented, task-irrelevant PLW affects the onset latency and accuracy of saccades to peripheral targets. We then use this paradigm to design experiments to study which aspects of biological motion-the global form mediated by the motion of the walker or the local movements of critical features-drive the observed attentional effects. Putting the two cues into conflict, we show that saccade latency and accuracy were affected by the local motion of the dots representing the walker's feet-but only if they retain their familiar, predictable location within the display.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.348
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of VisionSame topicAction Observation and SynchronizationFrench-language works237,207