Bibliographic record
Abstract
The objective of this study was to investigate the pollution assessment of organic matters, nutrients, and metals in sediment in major lakes (5 lakes and 17 sites) of Buk-han river using various sediment pollution assessment guidelines and indices. The concentrations of organic matters and nutrients were lower than class IV (Sediment pollution assessment guidelines of Korea) and Severe Effect Level (SEL, Sediment pollution assessment guidelines of Ontario). This results indicated that the lakes sediments were unpolluted and tolerable level for sediment dwelling organisms by organic matters and nutrients. However, several sites of Chuncheon and Soyang lakes were evaluated “heavily polluted” level by organic index (Org-index). The order of lakes by metals concentrations from the one with the highest concentration was Hwacheon, Chuncheon, Cheongpyeong, Uiam, Soyang. All lakes except Hwacheon were assessed unpolluted to marginally and tolerable level for sediment dwelling organisms by metals based on sediment pollution assessment guidelines (Korean and Ontario), indices of geoaccumulation (Igeo), pollution loading (PLI) and ecological risk (RI). In Lake Hwacheon, every investigated sites were polluted with metals, especially Hg, based on sediment pollution assessment guideline of Korea and indices (Igeo, PLI and RI). The dwelling organisms in sediment of Hwacheon Lake were likely to be severed by metals.
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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 | 0.000 |
| 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".