The onboard imagers for the Canadian ACE SCISAT‐1 mission
Bibliographic record
Abstract
The Atmospheric Chemistry Experiment (ACE) onboard the Canadian Space Agency’s SCISAT‐1 satellite has been in orbit since August of 2003. Its broad objective is to study the problem of stratospheric ozone depletion, particularly in the Arctic. The main instruments are two spectrometers, one an infrared Fourier Transform Spectrometer and the other a dual optical spectrophotometer sensitive in the UV and visible. Also included are two filtered imagers used to measure altitude profiles of atmospheric extinction and detect thin clouds. The nominal center wavelengths of the filters are 525 nm for the visible (VIS) imager and 1020 nm for the near‐infrared (NIR) imager. With the decommissioning of other satellite instruments used to monitor global aerosols [i.e., Stratospheric Aerosol and Gas Experiment II (SAGE II), SAGE III, Polar Ozone and Aerosol Measurement (POAM) III, Halogen Occultation Experiment (HALOE)], the imagers provide much needed continuity in this data record. The data product from the imagers is still, however, in a preliminary state. Funding restrictions in the prelaunch period were responsible for an incomplete characterization of the imagers’ optics and electronics and prevented corrections being made for the problems found during testing. Postlaunch data analysis to correct for image artifacts is ongoing. A comparison with coincidental measurements from SAGE II shows that systematic errors from the preliminary analysis are within 5 and 20% for the VIS and NIR imagers, respectively, for uninverted profiles of optical depth. Despite the preliminary nature of the imager results, a paper describing the imagers and the initial operational data processing code is timely because the data are already being used.
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 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 | 0.005 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".