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Record W1988510761 · doi:10.1145/1358628.1358728

Emotional response as a measure of human performance

2008· article· en· W1988510761 on OpenAlexaff
Danielle Lottridge

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsUniversity of Toronto
FundersInstitut national de recherche en informatique et en automatique (INRIA)
KeywordsComputer scienceStoryboardValence (chemistry)Human–computer interactionCognitionAffective computingKey (lock)UsabilityArousalMeasure (data warehouse)MultimediaPsychology

Abstract

fetched live from OpenAlex

Emotional reactions are a key part of the user experience, and are particularly of interest to the design of systems that consider user emotions. This dissertation studies methods of measuring emotional responses through a novel two-dimensional tool, based on the model of valence and arousal. A study on reactions to storyboard and video prototypes motivated the need for continuous, quantitative, affective self-report. A pilot study with a slider revealed significant differences between the experiences of several video conferencing techniques. Next steps include prototyping two-dimensional affective self-report capture devices, and an experiment to compare relative ease of use and cognitive complexity of different methods of emotional measurement.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.096
GPT teacher head0.352
Teacher spread0.256 · 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

Citations17
Published2008
Admission routes1
Has abstractyes

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