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Record W2081992857 · doi:10.1080/15367960802301077

ARIA Live Regions: An Introduction to Channels

2009· article· en· W2081992857 on OpenAlexaff
P. A. Thießen, Charles L. Chen

Bibliographic record

VenueJournal of Access Services · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsUniversity of Toronto
FundersMozilla Foundation
KeywordsAjaxWorld Wide WebComputer scienceMarkup languageWeb 2.0Web pageHTMLMultimediaWeb applicationWeb developmentWeb designXML

Abstract

fetched live from OpenAlex

Web 2.0, enabled by the AJAX architecture, and has given rise to new levels of user interaction with Web pages. Many of these new extremely popular Web 2.0 pages are better classified as full-fledged applications; for example, Google Maps, Google Docs, Flickr, and so on. Unfortunately, accessibility support in most AJAX applications is lacking. WAI-ARIA markup presents a solution to making these applications accessible. This paper presents a real-life example of how ARIA Live Regions can greatly improve the accessibility of a Web 2.0 chat application (ReefChat) when used with a WAI-ARIA aware assistive technology (Fire Vox).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0060.012
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0870.040

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 head0.042
GPT teacher head0.368
Teacher spread0.326 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations7
Published2009
Admission routes1
Has abstractyes

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