Development of a New Pilot Workload Rating Scale
Bibliographic record
Abstract
Pilot workload assessment has been a keen area of research for many years and has key applicability in flight testing. This paper outlines the development of a novel workload rating scale and index, the Comeau-Duggan Pilot Workload Index, which bridges gaps, such as causal factor identification, between some of the most widely used rating scales in flight test. The conceptualization and evolution of this index has been a multi-year and multi-nation research effort that has built upon the foundation and fundamental principles that underpin current widely accepted workload rating scales used in Human Factors and Handling Qualities engineering. The pilot workload index facilitates a rigorous and robust methodology for identifying the factors contributing to a given flying task, quantifying their impact through a structured suffix flowchart approach. It can provide, for example, a quantifiable link between pilot workload and the operational use of the aircraft, and therefore could inform aircraft and system design, as well as tactics and procedural development. It was developed through flight trials conducted at the National Research Council of Canada and flight simulator trials conducted at the University of Liverpool.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".