Spatial patterns of DOC concentration and DOM optical properties in a Brazilian tropical river‐wetland system
Bibliographic record
Abstract
Abstract The Cerrado (savanna) and Pantanal (wetland) biomes of Central Western Brazil have experienced significant development activity in recent decades, including extensive land cover conversion from natural ecosystems to agriculture and urban expansion. The Cuiabá River transects the Cerrado biome prior to inundating large areas of the Pantanal, creating one of the largest biodiversity hot spots in the world. We measured dissolved organic carbon (DOC) and the optical absorbance and fluorescence properties of dissolved organic matter (DOM) from 40 sampling locations spanning Cerrado and Pantanal biomes during wet and dry seasons. In the upper, more agricultural region of the basin, DOC concentrations were highest in the rainy season with more aromatic and humified DOM. In contrast, DOC concentrations and DOM optical properties were more uniform for the more urbanized middle region of the basin between wet and dry seasons, as well as across sample locations. In the lower region of the basin, wet season connectivity between the river and the Pantanal floodplain led to high DOC concentrations, a fourfold increase in humification index (HIX) (an indicator of DOM humification), and a 50% reduction in the spectral slope (SR). Basin‐wide, wet season values forSR, HIX, and FI (fluorescence index) indicated an increasing representation of terrestrially derived DOM that was more humified. Parallel factor analysis identified two terrestrially derived components (C1 and C2) representing 77% of total fluorescing DOM (fDOM). A third, protein‐like fDOM component increased markedly during the wet season within the more urban‐impacted region.
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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) | 0.001 | 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".