Pre and Post Pilot Model Analysis Compared to Experimental Simulator Results.
Bibliographic record
Abstract
‡In 2003, a workshop on the use of pilot models to analyze the influence of visual and vestibular motion perceptio n on a pilot’s control behavior was held. As an example, an earlier experiment on the Vertical Motion Simulator ( VMS ) at NASA Ames was used to demonstrate that a pilot model analysis could reasonably explain the trends of the experimental results. Mo re importantly, the same analysis suggested an experimental configuration that, if tested, might have changed the general conclusions found in the NASA Ames study. Useful progress in research is enhanced when new studies and analyses build upon previous st udies and analyses. A new simulator experiment built upon the NASA Ames study and also evaluated all the new conditions analyzed with the pilot model during the workshop noted above. The results roughly correspond with the analysis. Although, the utmost w as done to produce the same motion cues in the University of Toronto research flight simulator as in the VMS experiment before, differences in the experimental results were found between the results of the NASA experiment and the University of Toronto experiment. The paper reviews the initial analysis, compares the analysis results with the new results from the new experiment, and readjust s the pilot mode l analysis with the new results. † ‡ p y
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 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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".