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Record W2016554734 · doi:10.1177/154193120705100450

Strategy Selection and Compliance: A Case-Study Using a Thermal-Hydraulic Process Microworld

2007· article· en· W2016554734 on OpenAlexaff
Olivier St-Cyr

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2007
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsTask (project management)Selection (genetic algorithm)Interface (matter)Process (computing)Compliance (psychology)Computer sciencePreferenceHuman–computer interactionGraphical user interfaceControl (management)Process managementIndustrial engineeringSimulationArtificial intelligenceSystems engineeringEngineeringPsychologyMathematics

Abstract

fetched live from OpenAlex

This paper focuses on the third phase of the Cognitive Work Analysis framework: strategies analysis. While CWA outlines the basic characteristics of strategies, little attention has been paid to the issues of strategy selection and compliance. This paper presents experimental data looking at these issues. Forty engineering university students performed a start-up task on a representative thermal-hydraulic process microworld. Participants were divided into two groups, each performing the task with a different graphical user interface. Three different strategies were available to control the simulation: Single, Decoupled, and Full. The only constraints imposed on strategy selection were the physical characteristics of the process simulation. A frequency count for each of the different strategies used by participants was cumulated. Results show a strong preference towards the Decoupled strategy. Results also show significant differences between the two interface groups. These results provided helpful insights on strategy selection and compliance and interface design.

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)0.010
metaresearch head score (Gemma)0.031
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 score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.356
Teacher spread0.300 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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