<title>SHIELDS: A battlespace Fraunhofer line discriminator for real-time aerosol cloud analysis</title>
Bibliographic record
Abstract
Fraunhofer Line Discrimination (FLD) is a passive optical spectroscopy technique with potential for battlefield remote sensing of aerosol targets, as well as other military and academic applications. The Spatial Heterodyne Interferometer for Emergent Line Discrimination Spectroscopy (SHIELDS) will provide real-time remote sensing using FLD. The unit will be contained in a man-portable box to provide heads-up detection of dangerous chemicals in target clouds. The spectrometer employed will be the monolithic Spatial Heterodyne Spectrometer (SHS). One SHIELDS unit will feature a monolithic SHS to look at the 589-nm Solar Fraunhofer doublet. A second monolith will be built, using novel designs, to look at several different Fraunhofer lines of interest, all in the visible (H-b, Mg, H-a). The finished monoliths will be tested on laboratory targets, and the final complete SHIELDS unit will be further tested in the field.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.069 | 0.026 |
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".