Estimating water balance components of tropical wetland lakes in the Pantanal dry season, Brazil
Bibliographic record
Abstract
Water balance studies with stable water isotopes have rarely been conducted in remote and tropical wetland areas. As such, little is known regarding the water balance and groundwater–surface water interaction in the Pantanal, one of the largest and most pristine wetlands in the world. We applied MINA TrêS, a water balance model utilizing stable water isotopes (δ18O, δ2H) and chloride (Cl-) to assess the dry-season hydrological processes controlling groundwater–surface water interactions and the water balance of six floodplain lakes in the northern Pantanal, Brazil. Qualitatively, all lakes exhibited similarity in hydrological controls. Quantitatively, they differed significantly due to morphological differences in controlling groundwater inflow and lake volume. Our approach is readily transferable to other remote and tropical wetland systems with minimal data input requirements, which is useful in regions with sparse hydrometric monitoring. Editor Z.W. Kundzewicz
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".