<title>FTIR-based airborne spectral imagery for target interrogation</title>
Bibliographic record
Abstract
DRDC Valcartier is continuing to developed infrared spectral imagery systems for a variety of military applications. Recently a hybrid airborne spectral imager / broadband imager system has been developed for ground target interrogation (AIRIS). This system employs a Fourier Transform Interferometer system coupled to two 8x8 element detector arrays to create spectral imagery in the region from 2.0 to 12 microns (830 to 5000 cm-1) at a spectral resolution of up to 1 cm-1. In addition, coupled to this sensor are three broadband imagers operating in the visible, mid-wave and long-wave infrared regions. AIRIS uses an on-board tracking capability to: dwell on a target, select multiple targets sequentially, or build a mosaic description of the environment around a specified target point. Currently AIRIS is being modified to include real-time spectral imagery calibration and application processing. In this paper the flexibility of the AIRIS system will be described, its concept of operation discussed and examples of measurements will be shown.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.213 | 0.105 |
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".