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Record W1833218127 · doi:10.1109/ccece.1993.332217

A parametric method for the evaluation of human-computer interfaces

2002· article· en· W1833218127 on OpenAlexaff
Vianney Côté, Jean-Pierre Martin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsInterface (matter)Computer scienceCalculatorSelection (genetic algorithm)Parametric statisticsField (mathematics)Quality (philosophy)Function (biology)Product (mathematics)User interfaceData miningHuman–computer interactionArtificial intelligenceMathematicsProgramming languageStatistics

Abstract

fetched live from OpenAlex

The paper proposes a method of interface quality evaluation intended for product selection and based on a checklist. The method is flexible, easily understood and covers all aspects of an interface. Creation of the list rests upon a selection of more than 300 ergonomic criteria drawn from published reports and research articles in the field of interface design and evaluation. The criteria are high-level and relatively independent of the type of interface and technology. Their collection has been organised according to a new synthetic classification scheme which bears upon the functional capabilities and friendliness factors of an interface. Furthermore, the proposed method uses a parametric model to calculate the overall quality of an interface as a function of the values and weights assigned to the criteria and classes. The user can also adjust the model behaviour by modifying its sensitivity parameters. The method of evaluation has been implemented in an electronic calculator.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.991

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.225
GPT teacher head0.460
Teacher spread0.235 · 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 teacher head, not a consensus.

Study designOther design
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

Citations0
Published2002
Admission routes1
Has abstractyes

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