A Multiwavelength Retrieval Approach for Improved OSIRIS Aerosol Extinction Retrievals
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
Abstract The Optical Spectrograph and InfraRed Imaging System (OSIRIS) on board the Odin satellite has been used to provide vertically resolved aerosol extinction since 2001. The OSIRIS version 5.07 aerosol product has been used in numerous studies and now provides a 17‐year record of global stratospheric aerosol. This work presents the new version 7 OSIRIS aerosol extinction retrieval. A multiwavelength aerosol extinction algorithm has been developed to reduce measurement geometry biases and improve extinction retrieval in the upper troposphere and lower stratosphere. The Chen et al. (2016, https://doi.org/10.5194/amt-9-1239-2016 ) cloud detection algorithm has been adapted for the OSIRIS wavelength range for improved cloud screening and polar stratospheric cloud detection, and comparisons after volcanic eruptions and with the CALIPSO‐GOCCP product show promising results. The version 7 product shows comparable agreement with version 5.07 when compared to coincident SAGE II and SAGE III measurements, and improved agreement with CALIPSO time series. The algorithm has been applied to the complete set of OSIRIS measurements, and the new data set is now publicly available.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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