Replication data for: Unprecedented spring 2020 ozone depletion in the context of 20 years of measurements at Eureka, Canada
Bibliographic record
Abstract
This dataset contains data from a number of instruments (and simulations from one model) in Eureka, Canada. The HDF files he contain measurements of HCl and NO2 from the Bruker FTIR (2016-2020), in the GEOMS file format. The HCl data can be found on the NDACC archive as well, and this version differs only in the data filter used (negative VMRs were included here). The CRL_* file contains range-scaled signal measured by the CANDAC Rayleigh-Mie-Raman Lidar for 16-21 March, 2020. Additional details in the file header. The GBS_* files contain BrO and OClO slant columns retrieved from UV Zenith-Sky DOAS measurements (2007-2020, spring data only). Additional details in the file header. The Pandora_* file contains ozone measurements from Pandora #144 (2019-2020, spring only). The ozone columns have been corrected for a temperature-dependent bias. Additional details in the file header. The tomcat_* files contain trace gas profiles over Eureka, simulated by the TOMCAT/SLIMCAT 3D chemical transport model (2000-2020). Additional details in tomcat_1QY_era5_eureka_README.txt
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.032 |
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".