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Record W2740725316 · doi:10.1080/13506285.2017.1352639

Eye movements can cause item-specific visual recognition advantages

2017· article· en· W2740725316 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueVisual Cognition · 2017
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSaccadePsychologyEye movementFixation (population genetics)RecallCognitive psychologyRecognition memoryVisual short-term memoryCommunicationMemoriaObject (grammar)Visual memoryNeuroscienceArtificial intelligenceCognitionComputer science

Abstract

fetched live from OpenAlex

Prior research suggests that spontaneous saccades localized towards blank regions of space during memory storage and recall improve memory for items at the saccade locations. In the present study, we examined whether a recognition advantage can be observed when a single, exogenously directed saccade occurs during memory maintenance. We manipulated whether participants made a saccade to an item’s previous location or maintained fixation, as well as whether tested items reappeared in their original location or not. The results of three experiments showed that visual recognition was better after a saccade to the location of a probed object than after no saccade or after a saccade to the location of a non-probed object, so long as saccades went to the to-be-tested location more often than chance. Taken together, our findings demonstrate that eye movements can elicit an item-specific recognition advantage in visual working memory.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.901

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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.098
GPT teacher head0.381
Teacher spread0.282 · 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