A New Bruker IFS 125HR FTIR Spectrometer for the Polar Environment Atmospheric Research Laboratory at Eureka, Nunavut, Canada: Measurements and Comparison with the Existing Bomem DA8 Spectrometer
Bibliographic record
Abstract
Abstract A new Bruker IFS 125HR Fourier transform spectrometer has been installed at the Polar Environment Atmospheric Research Laboratory at Eureka, Nunavut, Canada (80.05°N, 86.42°W). This instrument will become the Network for the Detection of Atmospheric Composition Change’s (NDACC’s) primary instrument at Eureka, replacing the existing Bomem DA8 Fourier transform spectrometer, and will operate throughout the sunlit parts of the year. This paper introduces the new instrument and describes the retrieval procedure, including a comprehensive error analysis. Total columns of O3, HCl, HF, HNO3, N2O, CH4, and CO are presented for the first full year of measurements (2007). Perturbations in the total column resulting from the presence of the Arctic polar vortex over Eureka and the chemical processes within it are visible, as are annual cycles driven by photochemistry and dynamics. Enhancements in the CO total column resulting from specific biomass burning smoke events can also be seen. An intercomparison between the existing Bomem DA8 and the new Bruker IFS 125HR was carried out in July 2007 and is presented here. The total columns derived from the two instruments are shown to be in excellent agreement, with mean differences for all gases of less than 2.3%.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".