Biogeochemistry of the dissolved organic matter (DOM) in the estuarine rivers of Bangladesh–Sundarbans under different anthropogenic influences
Bibliographic record
Abstract
The Bangladesh-Sundarbans is the Outstanding Universal Value (OUV) articulated by UNESCO, is under different anthropogenic stress. The present study focused on the status of estuarine biogeochemistry of the dissolved organic matter (DOM) of the Bangladesh-Sundarbans using different optical methods. Four fluorophores: Peak A (230-265/408-488 nm), Peak M (290/414 nm), Peak C (365/488 nm), and Peak W (320/410 nm), and three fluorescent dissolved organic matter (fDOM) components (two humic-like, one detergent-like) were identified in the Sundarban mangrove Rivers by Excitation-Emission Matrix (EEM) and Parallel Factor (PARAFAC) analyses. Among the three components, the terrestrial-derived humic-like Component had a high intensity in five samples among six in the Bangladesh-Sundarbans. The total fluorescent intensity and calculated dissolved organic carbon (DOC) concentration were maximum in Harbaria and minimum in Kotka and Dublar char, respectively. Synchronous fluorescence spectroscopy (SFS) identified protein-like component besides humic-like DOM. The optical indices described that natural fDOM components were from terrestrial sources, were matured, and autochthonous fDOM production was low. The DOM components were relatively lower in molecular size and aromaticity in Harbaria. However, water samples in Harbaria contained organometallic compounds that had much absorbance at 254 nm wavelength. DOM components had low energy and more π-conjugated molecules in structure in the Dublar char and Kotka. Components in Dublar char had comparatively higher molecular size and weight than other sampling stations. The Harbaria and Mongla port contained more hydrophobic and less polar substances than other stations. This study will firmly add diversified notions to future research regarding mangrove forest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.010 | 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 teacher head, 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".