Remote sensing of stratospheric aerosols during intense forest fire using SAGE 3 data
Bibliographic record
Abstract
During summer 2003, large areas of the West Canada (Alberta and British Columbia between 50°N and 60°N and between 105°W and 130°W) have undergone very important forest fires, which were detected by Total Ozone and Mapping Spectrometer (TOMS) and MODerate resolution Imaging Spectroradiometer (MODIS). Many Stratospheric Aerosol and Gas Experiment (SAGE) III measurements obtained during this summer and over this region exhibit enhanced aerosol extinctions in the low stratosphere. SAGE III instrument measures the transmitted light through the earth limb using the solar occultation method. Inversion of transmission measurements allows retrieving vertical profiles of concentration of minor gases and vertical profiles of aerosol extinction coefficient at several wavelengths (from 384 to 1545 nm) in the stratosphere. We have analyzed the aerosol spectral extinctions measured during correlative SAGE III events to observe the impact of these biomass burnings on the properties of stratospheric aerosols. We have inferred the aerosol microphysical properties (effective radius, number density, surface area density) assuming two different compositions corresponding to background (sulphate) and biomass burning aerosols. We have also compared the results to values obtained during unperturbed periods. It is found that a large number of aerosols was injected in the stratosphere but we cannot distinguish between both types of aerosols.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".