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Record W1977285608 · doi:10.1109/smc.2014.6973928

Revisiting three ecological interface design experiments to investigate performance and control stability effects under normal conditions

2014· article· en· W1977285608 on OpenAlexaff
Chelsea Carrasco, Greg A. Jamieson, Olivier St-Cyr

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTask (project management)Context (archaeology)Stability (learning theory)Interface (matter)Control (management)Noise (video)Computer scienceContrast (vision)CognitionCognitive psychologyPsychologyArtificial intelligenceEngineeringMachine learningImage (mathematics)Geography

Abstract

fetched live from OpenAlex

This paper seeks to: (1) provide statistical evidence regarding operator task performance and control stability during the learning phase of two archival experiments in which participants in EID and non-EID interface groups were balanced by cognitive style; and (2) to compare task performance and control stability from these two experiments and a third archival experiment differentiated by the presence or absence of early faults and sensor noise. Participants in the EID condition of the first two studies 1) achieved target goals significantly faster, and 2) exhibited more stable control than those in the non-EID condition. When considered in context of the third study, the results again showed participants in the EID condition outperformed those in the non-EID condition. These results stand in contrast to previously reported findings, wherein no task performance differences were observed between these interface conditions.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

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)0.0070.001

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 head0.053
GPT teacher head0.359
Teacher spread0.306 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2014
Admission routes1
Has abstractyes

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