Brewer, SAOZ and ozonesonde observations in Siberia
Bibliographic record
Abstract
Daily total ozone measurements are carried out in Tomsk, Central Siberia using Brewer Mark-IV spectrophotometer 049 since 2003. This instrument was used at Heiss Island, Franz Josef Land, Russia in 1988-1994. The accuracy of routine total ozone observations at direct sun measurements is 2-3%. Under cloudless conditions at air mass factor less than 4, the accuracy of total ozone direct sun measurements approaches 1%, while the accuracy of direct moon observations is 2-3%. SAOZ (Systeme d'Analyse par Observation Zenitale) is UV-visible (300-650 nm) diode array spectrometer developed at the Service d'Aeronomie, CNRS, France for monitoring stratospheric ozone and NO2. Zenith sky measurements of atmospheric gases at twilight (86°< solar zenith angle < 91°) are used. There are 17 SAOZ instruments in SAOZ network around the world. Ttree instruments are located at the Arctic Circle in Russia at Zhigansk since 1992, Salekhard since 1998 and Anadyr station in Far East, Russia since January 2011. Accuracy of total ozone measurements is 6% and 10% for nitrogen dioxide observations. The results of ozone monitoring are compared with data of ozone measurements in polar vortex conditions at these stations are in SAOZ database. Currently, we use 2Z-ECC ozonesondes for ozone profile observations in winter/spring periods at Salekhard aerological station. The results of ozonesounding at Salekhard station are in NDACC database. The recent results of Brewer, SAOZ total ozone observations in Siberia and Far East, Russia, data of ozone profile observations in western Siberia at Salekhard aerological station in winter/spring sesons of 2011 and 2012 will be presented and discussed.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".