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Record W2332275336 · doi:10.1177/154193120004403715

Web-Based Collection of Critical Incidents during Remote Usability Evaluation

2000· article· en· W2332275336 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.

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2000
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsUsabilityComputer scienceData collectionWeb applicationUser interfaceWorld Wide WebWeb usabilityHuman–computer interactionOperating system

Abstract

fetched live from OpenAlex

A web-based reporting tool was developed to support the collection of critical incidents during remote usability evaluations. The tool facilitated structured critical incident data entry by the user and the ability to transfer this data directly to the experimenter in the form of an email. The reporting tool was evaluated by assessing a voice email system comprised of a voice interface for emailing and a web interface for system configuration. The evaluation compared the frequency and severity of critical incidents obtained from remote participants with users located in a controlled laboratory setting. Changes in critical incident reporting resulting from repeated exposure to the system were evaluated. The results of the evaluation demonstrated that the web-based reporting tool was an effective critical incident data collection technique for remote usability evaluation.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.273
Teacher spread0.247 · 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