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
We examined the eye movements of pilots as they carried out simulated aircraft landings under day and night lighting conditions. Our five students and five certified pilots were instructed to quickly achieve and then maintain a constant 3-degree glideslope relative to the runway. However, both groups of pilots were found to make significant glideslope control errors, especially during simulated night approaches. We found that pilot gaze was directed most often toward the runway and to the ground region located immediately in front of the runway, compared to other visual scene features. In general, their gaze was skewed toward the near half of the runway and tended to follow the runway threshold as it moved on the screen. Contrary to expectations, pilot gaze was not consistently directed at the aircraft's simulated aimpoint (i.e., its predicted future touchdown point based on scene motion). However, pilots did tend to fly the aircraft so that this point was aligned with the runway threshold. We conclude that the supplementary out-of-cockpit visual cues available during day landing conditions facilitated glideslope control performance. The available evidence suggests that these supplementary visual cues are acquired through peripheral vision, without the need for active fixation.
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