Studying Collision Avoidance by Nearly Colliding
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.
Bibliographic record
Abstract
As the next generation of air traffic systems (NextGen) moves forward, human factors analyses related to warnings and graphical depictions of air traffic conflicts become increasingly important. Despite this, related human-factors research involving traffic has been conducted in simulation where the contributions of traffic display systems and ultimately visual detection of traffic cannot be fully assessed. We report a flight trial involving 12 deliberate near miss (as little as 160 ft) configurations of differing intercept angles. We evaluate the workload and track error of the intruder test pilot for flight trials in which a custom iPod™ Automatic Dependent Surveillance-Broadcast (ADS-B)-driven display was used. Constant and variable error of trajectory tracks were differentially affected by the availability of three-dimensional real world information for the intercept approach. We consider the components of spatial representation common to planned interceptions and traffic avoidance and discuss the implications for the design of cockpit display of traffic information (CDTI) systems and the role of automation in collision avoidance systems.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it