Passive remote monitoring of multi-gas mixtures by FTIR radiometry
Bibliographic record
Abstract
The passive remote monitoring of multi-gas vapour mixtures by FTIR spectroscopy is investigated experimentally. The spectral radiance data were collected with the CATSI interferometer for a variety of multi-gas plumes at a distance of 60 m. Two basic sets of mixtures were studied. The first set corresponds to mixtures formed of three gases with no overlapping spectral bands (C2H2, C2H4 and R14). The second set corresponds to mixtures formed of three gases having overlapping spectral bands (C2H4, R114 and R134a). For each mixture the flow rates of individual constituents were adjusted to yield specific constituent CL ratios. These ratios are compared to the CL ratios retrieved from infrared radiance spectra. Results of this study indicate that for both sets of multi-gas mixtures the CL ratios retrieved by the passive remote monitoring technique agree well with those derived from the release flow rates. This good level of agreement was achieved by introducing a simple correction scheme to compensate for the limited accuracy of the fast radiance model implemented in the GASEM monitoring algorithm.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".