Geochemical Evolution of Groundwater Flowing Through Arsenic Source Sediments in an Aquifer System of West Bengal, India
Bibliographic record
Abstract
Abstract The source of geogenic arsenic (As) contaminating a shallow aquifer in West Bengal was traced to fine‐grained sediments deposited in an abandoned river channel. Along with As‐bearing phases, these sediments contain 0.46% codeposited organic carbon. The release of As and the geochemistry of groundwater within the channel‐fill deposits is investigated using a detailed mass balance model supported by aqueous, solid‐phase, and mineralogical data. The model describes the evolution of groundwater chemistry along a flow path extending from its recharge in an abandoned channel pond, through the channel fill, to the underlying aquifer. Variations in groundwater composition are explained in terms of mineral weathering of host sediments driven by organic carbon decay. Arsenic is released through the reductive dissolution of goethite and the weathering of chlorite. Concomitantly, some As is sequestered in precipitating vivianite. These competing processes reach equilibrium deeper in the channel‐fill sequence as groundwater As concentrations stabilize. The model yields estimates of mineral reaction (or precipitation) rates including rates of organic carbon oxidation (1.15 mmol C L−1 a−1) and net As release ( mmol L−1 a−1). Fine‐grained, slightly permeable, deposits such as channel fill containing reactive organic carbon and As‐bearing goethite and phyllosilicates are centers of intense chemical weathering conducive to As mobilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.001 | 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".