Quality control of CarboEurope flux data – Part 2: Inter-comparison of eddy-covariance software
Bibliographic record
Abstract
Abstract. As part of the quality assurance and quality control activities within the CarboEurope-IP network, a comparison of eddy-covariance software was conducted. For four five-day datasets, CO2 flux estimates were calculated by seven commonly used software packages to assess the uncertainty of CO2 flux estimates due to differences in post-processing. The datasets originated from different sites representing different commonly applied instrumentation and different canopy structures to cover a wide range of realistic conditions. Data preparation, coordinate rotation and the implementation of the correction for high frequency spectral losses were identified as crucial processing steps leading to significant discrepancies in the CO2 flux results. The overall comparison indicated a good although not yet perfect agreement among the different software within 5–10% difference for 30-min CO2 flux values. Conceptually different ideas about the selection and application of processing steps were a main reason for the differences in the CO2 flux estimates observed. A balance should be aspired between scientific freedom on the one hand, in order to advance methodical issues, and standardisation of procedures on the other hand, in order to obtain comparable fluxes for multi-site synthesis studies.
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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 | 0.030 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".