Organic matter and dissolved inorganic nitrogen in estuarine muddy deposits. Aquatic Ecosystem Health and Management
Bibliographic record
Abstract
Organic matter (OM) and dissolved inorganic nitrogen (DIN: nitrite, nitrate and ammonium) in the sediments as well as in the water column of two temperate estuaries, the Scheldt Estuary in Belgium and the Netherlands, and the Fraser Estuary in Canada, were investigated. Three representative stations, differing in salinity and representing areas of fast sedimentation, were selected in each estuary. Samples were taken during periods of high and low river discharge. The results show, in both estuaries, that the vertical distributions of OM and DIN in a sediment layer are affected by the instability, caused by episodic resuspension and re-deposition, of the uppermost sediment layer. The findings of this study suggest a hypothesis, next to biogeochemical processes, that the OM and DIN distributions in upper sediment layers are influenced by sedimentary processes in the estuarine environment. The same sedimentary processes even in different estuaries affect OM and DIN distributions in an equivalent way. Correspondingly, the similarity or difference in OM and DIN distribution to a certain extent reflects the sedimentary dynamics. River runoff and sediment resuspension and sedimentation have important impacts on sediment behaviour and thus regulate OM and DIN distributions and shape their vertical profiles in the sediments. As a reflection, the coupling of sediment resuspension followed by redeposition can be deduced from the vertical profile of DIN in the bottom sediments which, in turn, can provide a time-integrated periodic record of the most recent sedimentary history.
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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 | 0.000 | 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".