Bibliographic record
Abstract
The Global Inundation Extent from Multi-Satellites-MethaneCentric (GIEMS-MC) provides two harmonized times series maps at 0.25°x0.25° and monthly time step of wetland surfaces from 1992 to 2020: one representing inundated and saturated wetlands, and the other covering all wetlands, including peatlands. In addition, GIEMS-MC provides consistent 0.25°x0.25° maps of rice paddies (from MIRCA2000) and open permanent water categories (from GLWDv2) used in its production. Information on the dominant vegetation type and wetland type per pixel is also provided. GIEMS-MC v1.1 is the version used in related publication :Bernard, J., Prigent, C., Jimenez, C., Fluet-Chouinard, E., Lehner, B., Salmon, E., Ciais, P., Zhang, Z., Peng, S., and Saunois, M.: The GIEMS-MethaneCentric database: a dynamic and comprehensive global product of methane-emitting aquatic areas, Earth Syst. Sci. Data, 17, 2985–3008, https://doi.org/10.5194/essd-17-2985-2025, 2025. The differences between GIEMS-MC v1.1 and v1.0 are minor. These include the inclusion of Deltas in ancillary information and the correction of typos.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.082 | 0.094 |
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".