CH4 Flux Dataset and Upscaling Maps for TVC, Canada, 2019–2024
Bibliographic record
Abstract
This is Version 2 of the dataset, which updates the main data file to dataset_v2 by adding a new column, Element_Type, for a more detailed classification of LC_geom. This dataset accompanies the study on methane (CH₄) flux upscaling and model comparison in Arctic wetlands of Trail Valley Creek, Northwest Territories, Canada, covering the period July 2019–2024. It includes in situ chamber measurements of CH₄ flux and geospatial model outputs All spatial files are provided as GeoTIFFs. The original tabular data is in Excel format. This dataset supports the reproducibility of the modeling pipeline and is suitable for further ecological, statistical, or remote sensing analyses. This dataset includes CH₄ flux measurements originally published in Voigt et al. (2023). Contact: Kseniia Ivanova (kivanova@bgc-jena.mpg.de). Citation required if used.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.026 |
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".