<title>Flight testing the infrared eye prototype</title>
Bibliographic record
Abstract
The Infrared (IR) Eye was developed with support from the National Search-and-Rescue Secretariat (NSS), in view of improving the efficiency of airborne search-and-rescue operations. The IR Eye concept is based on the human eye and uses simultaneously two fields of view to optimize area coverage and detection capability. It integrates two cameras: the first, with a wide field of view of 40 degree(s), is used for search and detection while the second camera, with a narrower field of view of 10 degree(s) for higher resolution and identification, is mobile within the wide field and slaved to the operator's line of sight by means of an eye-tracking system. The images from both cameras are fused and shown simultaneously on a standard high resolution CRT display unit, interfaced with the eye-tracking unit in order to optimize the man-machine interface. The system was flight tested using the Advanced System Research Aircraft (Bell 412 helicopter) from the Flight Research Laboratory of the National Research Council of Canada. This paper presents some results of the flight tests, indicates the strengths and deficiencies of the system, and suggests future improvements for an advanced 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".