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Record W2119136420 · doi:10.1080/01449290110069400

Optimizing the reading of electronic text using rapid serial visual presentation

2001· article· en· W2119136420 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

VenueBehaviour and Information Technology · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPunctuationRapid serial visual presentationSentenceComputer scienceReading (process)PreferencePresentation (obstetrics)Word (group theory)Focus (optics)Speech recognitionArtificial intelligencePsychologyLinguisticsCognitionNeuroscienceMedicineMathematics

Abstract

fetched live from OpenAlex

The focus on communications technology in recent years has led to the question of how to best display electronic text onto small-screened devices. Past studies have shown that the compact method of rapid serial visual presentation (RSVP) is efficient but not well liked. Two experiments were conducted to explore ways of improving the preference for and feasibility of RSVP. In experiment 1, the effects of a completion meter, punctuation pauses, and variable word duration were studied. Although the sentence-by-sentence and normal page formats were still superior, post-experiment ratings indicated that punctuation pauses improved user preference for RSVP, and its preference increased in general with practice. In experiment 2, a modified RSVP condition included a completion meter, punctuation pauses, interruption pauses and pauses at clause boundaries. This condition was significantly preferred to a normal RSVP condition. The present enhancements may increase the feasibility of using RSVP with small displays.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.333
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