Stratospheric aerosol retrieval with optical spectrograph and infrared imaging system limb scatter measurements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An algorithm for the retrieval of global stratospheric aerosol profiles is presented using the optical spectrograph and infrared imaging system limb scatter measurements as an example data set. The retrieval utilizes a one‐dimensional version of the MART nonlinear relaxation inversion suitable for limb scatter. A height profile of the particle size distribution must be assumed in order to retrieve the aerosol number density. An altitude normalized wavelength ratio measurement vector is employed to minimize effects of upwelling radiation from ground albedo and uncertainties in the neutral density profile. Using a method of numerical perturbation, a formal error analysis is performed that shows that the dominant error term is the measurement noise. Comparison with stratospheric aerosol and gas experiment (SAGE) II and SAGE III coincident measurements of extinction shows agreement with the limb scatter retrievals to within 15% throughout the lower stratosphere for an appropriate choice of particle size distribution. The relatively high sampling resolution of the limb scatter technique makes this data set of interest for studying the dynamics of the stratosphere, stratosphere/troposphere exchange, and for extending the long history of the aerosol data record from the SAGE series of occultation measurements.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it