Imaging Systems in Search and Rescue: Implications for Geographic Orientation
Bibliographic record
Abstract
Optical imaging systems have the potential to dramatically change the task of a search and rescue technician. An important difference between the traditional process of “looking out the window” and search conducted with the aid of an optical imaging system is that in the case of imaging systems the frame of reference for the viewed display is de-coupled from the technician's frame of reference. We examined the ability of a moving-map display that recorded the locations of designated targets to support geographic orientation in operators with and without knowledge of the modeled terrain. Participants who did not have knowledge of the terrain benefited from the moving map, as when it was present they were less likely to re-identify targets that they had already viewed, whereas those who were already familiar with the terrain model showed no benefit from this manipulation. Both groups had difficulty localizing targets on a map following flight, and the two groups did not differ in their ability to initially detect targets using the system.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".