Building the COllaborative Carbon Column Observing Network(COCCON): Long term stability and ensemble performance of theEM27/SUN Fourier transform spectrometer
Bibliographic record
Abstract
Abstract. In a 3.5 year long study, the long term performance of a mobile Bruker EM27/SUN spectrometer, used for greenhouse gases observations, is checked with respect to a co-located reference Bruker IFS 125HR spectrometer, which is part of the Total Carbon Column Observing Network (TCCON). We find that the EM27/SUN is stable on timescales of several years, qualifying it as an useful supplement for the existing TCCON network in remote areas. For achieving consistent performance, such an extension requires careful testing of any spectrometers involved by application of common quality assurance measures. One major aim of the COllaborative Carbon Column Observing Network (COCCON) infrastructure is to provide these services to all EM27/SUN operators. In the framework of COCCON development, the performance of an ensemble of 30 EM27/SUN spectrometers was tested and found to be very uniform, enhanced by the centralized inspection performed at the Karlsruhe Institute of Technology prior to deployment. Taking into account measured instrumental line shape parameters for each spectrometer, the resulting average bias across the ensemble in XCO2 is 0.20 ppm, while it is 0.8 ppb for XCH4. As indicated by the executed long-term study on one device presented here, the remaining empirical calibration factor deduced for each individual instrument can be assumed constant over time. Therefore the application of these empirical factors is expected to further improve the EM27/SUN network conformity beyond the raw residual bias reported above.
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.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".