Simple laboratory methods for quantitative IR measurements of CW agents
Bibliographic record
Abstract
A simple method is presented for quantitatively measuring the absorbance of chemical warfare (CW) agents and their simulants in the vapour phase. The technique is based on a standard lab-bench FTIR spectrometer, 10-cm gas cell, a high accuracy Baratron pressure manometer, vacuum pump and simple stainless-steel hardware components. The results of this measurement technique are demonstrated for sarin (GB) and soman (GD). A second technique is also introduced for the passive IR detection of CW agents in an open- air path located in a fumehood. Using a modified open-cell with a pathlength of 45 cm, open-air passive infrared measurements have been obtained for simulants and several classical CW agents. Detection, identification and quantification results based on passive infrared measurements are presented for GB and the CW agent simulant, DMMP, using the CATSI sensor which has been developed by DRDC Valcartier. The open-cell technique represents a relatively simple and feasible method for examining the detection capability of passive sensors, such as CATSI, for CW agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".