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Record W2131582658 · doi:10.1080/02643290126100

Backward Pattern Masking of Familiar and Unfamiliar Materials in Disabled and Normal Readers

2001· article· en· W2131582658 on OpenAlexaff
Richard S. Kruk, Dale M. Willows

Bibliographic record

VenueCognitive Neuropsychology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of TorontoUniversity of Manitoba
Fundersnot available
KeywordsPsychologyBackward maskingVisual maskingStimulus onset asynchronyAudiologyStimulus (psychology)Masking (illustration)PerceptionCognitive psychologyVisual perceptionCommunicationNeuroscience

Abstract

fetched live from OpenAlex

A discrimination task involving backward pattern masking was designed to investigate differences between disabled and normal readers in text perception. Masking was observed for both groups with unfamiliar Japanese materials, but disabled readers were less sensitive in discriminating than were normal readers. The same result was obtained with Roman letters, despite the high familiarity of materials to both groups, and with nonwords and words. A significant interaction between group and stimulus onset asynchrony, indicating that disabled readers recovered from masking at a slower rate than normal readers, was found only with nonwords. Visual factors alone could not have mediated group differences. A subgroup of disabled readers, formed on the basis of susceptiblity to masking, showed evidence of a deficit in rate of visual processing. The results are likely due to differences in the quality of representations of visual information used in discrimination and in word recognition.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.312
Teacher spread0.266 · 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 designObservational
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

Citations9
Published2001
Admission routes1
Has abstractyes

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