Current ground-based LWIR his remote sensing activities at Defense R&D Canada — Valcartier
Bibliographic record
Abstract
Recently, DRDC Valcartier has been investigating novel ground-based longwave hyperspectral imaging (HSI) remote sensing techniques. Specific projects include the development of a new ground-based sensor called MoDDIFS (Multi-Option Differential Detection and Imaging Fourier Spectrometer), which is a leading edge infrared (IR) hyperspectral imaging (HSI) sensor optimized for the standoff detection of explosive vapours and precursors. The development of the MoDDIFS sensor is based on the integration of two innovative technologies: (1) the differential Fourier-transform infrared (FTIR) radiometry technology found in the Compact Atmospheric Sounding Interferometer (CATSI) previously developed by DRDC Valcartier, and (2) the HSI technology developed by Telops. The MoDDIFS sensor will offer the optical subtraction capability of the CATSI system but at high-spatial resolution using an MCT focal plane array of 84×84 pixels. The MoDDIFS sensor offers the potential of simultaneously measuring differential linear polarizations to further reduce the clutter in the measured radiance.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".