Hydrochemistry of a coastal sedimentary basin: evidence from the Lower Kutai Basin, Indonesia
Bibliographic record
Abstract
Groundwater is a vital freshwater resource in coastal regions, where 38 % of the global population currently resides. The hydrochemistry of abstracted groundwater in low-lying deltaic regions can pose a risk to human health, especially where monitoring of groundwater quality is limited. This study investigates new evidence of the hydrochemistry of shallow (depths of <250 m) groundwater in the Lower Kutai Basin (LKB) where Indonesia's new capital, Nusantara, is situated. Shallow groundwater is predominantly (67 out of 73 samples) fresh with a median total dissolved solids of 197 mg/L and hydrochemical facies are dominated by the bicarbonate anion. In this coastal sedimentary basin, high concentrations of iron (median = 5.4 mg/L) and manganese (median = 138 μg/L) that exceed WHO drinking-water guidelines reflect widespread reducing conditions in shallow groundwater, promoted by sluggish flow under low hydraulic gradients (primarily <0.002). Stable isotope ratios (δ 18 O, δ 2 H) indicate that inland fresh groundwater, traced to heavy rainfall, becomes isotopically heavier and more saline toward the coast. Although the hydrochemical conditions favoring arsenic mobilization mirror those of Asian megadeltas, arsenic concentrations in the shallow groundwater of the LKB are generally low (median = 0.5 μg/L).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".