Novel Application of FTIR Spectroscopy for the Passive Standoff Detection of Radiological Materials
Bibliographic record
Abstract
Abstract : An investigation is made into the possibility of applying the long-wave passive standoff detection technique to the identification of radiological materials. This work is based on laboratory measurements of the diffuse reflectance from a number of radiological or related products, including UO2, UO3, U3O8, CoO, Co2O3, IrO2, ThO2, SrO, I2O5, La2O3, and yellow cake. The measured laboratory reflectance signatures were incorporated into the MODTRAN4 radiative transfer model to simulate the nadir radiances of various radiological compounds for three different sensor altitudes. The results of the simulations suggest that passive standoff radiometry may potentially detect and identify radiological materials. Further evidence to support the applicability of the method is based on measurement results from a field trial held at Defence Research and Development Canada-Valcartier involving the passive detection of SrO at standoff distances of 10-40 m.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".