Carbon monoxide and trends and Events from two decades of the MOPITT instrument
Bibliographic record
Abstract
<!--!introduction!--> On 18th December 1999, the Terra platform was launched from the Vandenberg Air Force base carrying the Measurements Of Pollution In The Troposphere (MOPITT) instrument measuring carbon oxide (CO). Although manifested for a 5-year mission, the Terra satellite and MOPITT have now completed more than 23.5 years of operation. The 23+ years of continuous data series from MOPITT provide a great opportunity for investigations all over the globe. The instrument has been very stable and throughout the mission, the data have been validated. The result is a well-characterised time record that can now be “mined” for a variety of phenomena. Over the time that MOPITT has measured, it appears that the global burden of CO is decreasing, but superimposed on this trend are episodic events, and some of these recent events – especially 2020 for both Australia and North America – have extremely high values. These events occurred in highly populated regions and therefore are important because of the societal and economic issues. This paper will explore whether these events are coming more frequent or not. MOPITT was built in Canada by COMDEV of Cambridge, ON, data processing is performed at the National Center for Atmospheric Research in Boulder, CO. The Terra satellite is funded and operated by NASA, and the MOPITT instrument and operations are funded by the Canadian Space Agency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".