Diatom dan Paleolimnologi: Studi Komparasi Perjalanan Sejarah Danau Lac Saint-Augustine Quebeq-City, Canada dan Danau Rawa Pening Indonesia
Bibliographic record
Abstract
Diatoms are a micro-alga dominates in the aquatic ecosystem. Their silicious cell wall able to preserve death diatoms in the sediment for long periods of time, therefore, diatoms have an important role in the paleolimnological analysis. Diatoms assemblages in the sediment layer express the water quality whenever the diatom lives. This article provides information how to apply diatom on the paleo-limnological analysis, supporting with the case study in the Lac Saint-Augustine Quebec-City Canada and Rawa Pening Lake Indonesia. Modern diatom and the water quality from spatial and temporal range are used as a calibration set. The diatoms of below layers, then, Weighted Averaging (WA) with the calibration set to reconstruct the water quality in the past. Previously, both in Canada and Indonesia, those lakes were oligotrophic and sharply change into eutrophic condition since a lot of human activities developed around the lakes (anthropogenic factors). Naturally, the maturity of lake can not avoid and the succession had been fast by eutrophication. Paleolimnological approach provides baseline data in the past to develop the appropriate lake management.
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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 | 0.001 | 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) | 0.002 | 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".