Supplementary material to "Ozonesonde climatology between 1995 and 2009: description, evaluation and applications"
Bibliographic record
Abstract
Impact of Applying the Correction FactorFor most ozone stations a correction factor is provided that is derived in scaling the entire ozone column to an independent measurement of ozone column measured by a Brewer-Dobson spectrometer.Profiles that have been corrected by a factor outside the range of 0.8 and 1.2 are often ignored to not employ profiles that are heavily corrected with regard to ozone column measured by Brewer 5 and Dobson spectrometers (WMO, 1995(WMO, , 1999)).Since the correction factor was scaled with regard to the entire column, it is not necessarily valid for the tropospheric part of the profile.A comparison between MOZAIC aircraft data and ozone sondes has shown that tropospheric comparisons are better when omitting such correction factors (Thouret et al., 1998).To dismiss profiles that have been corrected by a factor outside the range of 0.8 and 1.2 has little 10 impact on the averaged ozone profiles between 1995 and 2009, as shown in Figure 1.Only those stations are shown, where the percentage difference between all profiles and only minor corrected profiles is larger than 0.5%.Differences up to 5-10% occur for a couple of stations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.349 | 0.127 |
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".