Calibration of instruments for atmospheric ozone measurements II: the ACE FTS and MAESTRO spectrograph
Bibliographic record
Abstract
A novel and simple technique is described for the calibration of satellite instruments for the measurement of atmospheric ozone. Ozone is generated in a gas cell and spectral measurements of the ozone absorption are measured with a standard Fourier-transform spectrometer (FTS) in order to determine the amount of ozone in the cell. The satellite instrument then views the cell using an appropriate illumination source. In this presentation the preliminary results from the ozone calibration procedure are presented for the ACE FTS and MAESTRO instruments to show how consistently both instruments measure ozone. The thermal infrared band of ozone at 4.7 microns was used to provide the calibration of the ACE interferometer, whereas the Chappuis band at 600 nm was used to characterize the response of the MAESTRO instrument. The ozone transmission spectra that were derived from the ACE FTS and MAESTRO spectrograph measurements were found to be in good agreement with the simulated spectra of known amounts of ozone from a radiative transfer model. All of the results yielded column ozone amounts that were within 10% of each other. These calibration measurements were taken at the University of Toronto in March 2003, before the expected launch date of the SciSat-1 satellite in August 2003.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".