Time-resolved thermal infrared multispectral imaging of gases and minerals
Bibliographic record
Abstract
For years, scientists have used thermal broadband cameras to perform target characterization in the longwave (LWIR) and midwave (MWIR) infrared spectral bands. The analysis of broadband imaging sequences typically provides energy, morphological and/or spatiotemporal information. However, there is very little information about the chemical nature of the investigated targets when using such systems due to the lack of spectral content in the images. In order to improve the outcomes of these studies, Telops has developed dynamic multispectral imaging systems which allow synchronized acquisition on 8 channels, at a high frame rate, using a motorized filter wheel. An overview of the technology is presented in this work as well as results from measurements of solvent vapors and minerals. Time-resolved multispectral imaging carried out with the Telops system illustrates the benefits of spectral information obtained at a high frame rate when facing situations involving dynamic events such as gas cloud dispersion. Comparison of the results obtained using the information from the different acquisition channels with the corresponding broadband infrared images illustrates the selectivity enabled by multispectral imaging for characterization of gas and solid targets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".