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Record W2079202277 · doi:10.1177/154193120504900115

Evaluating control activity as a measure of workload in flight test

2005· article· en· W2079202277 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 · 2005
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsWorkloadMetric (unit)SimulationTest (biology)Control (management)Measure (data warehouse)Computer scienceEngineeringOperations managementArtificial intelligenceOperating systemData mining

Abstract

fetched live from OpenAlex

This paper describes an investigation of a workload measurement technique based on pilot control movements. The Dynamic Interface Modeling and Simulation System Product Metric (DIMSS PM) assumes that pilot control activity can be used to evaluate pilot workload. Three qualified test pilots flew the fly-bywire NRC Bell 205 helicopter in a short test program that compared the DIMSS PM with subjective workload ratings and handling qualities ratings. The pilots performed a variation of an ADS-33E bob-up with varying levels of simulated turbulence and modified cyclic control characteristics. Good agreement was found for most in-flight test conditions between DIMSS Workload Metric scores and subjective workload ratings from the Bedford Workload Scale and Cooper-Harper handling qualities ratings. While, the DIMSS Workload Metric did not accurately reflect workload increases due to variations in the cyclic stick characteristics, the metric shows promise as an objective measurement tool of pilot workload in well-defined tests.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.242
Teacher spread0.228 · 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