Paleolimnological Investigations in Coastal Sarıkum Lagoon, Sinop, Turkey
Bibliographic record
Abstract
Lagoons are dynamic systems, making ecosystem management difficult. Paleolimnological approach is the only way to track past long term environmental changes and background conditions that are essential to build environmental management plans. Here, we investigated a sediment record from Sarıkum Lagoon, on the Black Sea coastal plain in North Anatolia, through a multiproxy paleolimnological approach to reveal long term environmental change and background conditions in the lake. For which, dry weight, organic and carbonate carbon, chlorophyll a (including its main diagenetic products), magnetic susceptibility and ostracod analysis were undertaken. The core was dated via radionuclide technique. At around 30 cm of the sediment record, there are abrupt transitions in all proxies, indicating a massive sediment input, a transition from transitional water to lacustrine environment, and lake’s biota also changed. Biological proxies preserved in the sediments suggest that the latest zone, after this event, is represented by lacustrine and hydrologically more isolated conditions from the Black Sea. Whatever the reason of that event (e.g. earthquake, flood), Sarıkum Lagoon has had lacustrine conditions during the last ~ 2 and half centuries following that abrupt event. This long term environmental change information should be considered while making future ecosystem management and conservation plans for the lake. (e.g. keep the lake connected with the Black Sea).
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".