낙동강 본류에 분포하는 표층 퇴적물의 지화학적 특성 변화
Bibliographic record
Abstract
To certificate change in the geochemical characteristics of surface sediments in the main stream of the Nakdong River, surface sediments from 12 sampling sites during the first and second half year (total 24 sampling sites) were collected and analyzed for grain size, ignition loss, total organic carbon and heavy metal content. Surface sediments mainly composed of sand (coarse and medium sand) and fining changed from the first half to the second half of the year. Ignition loss, total organic carbon and heavy metals content increased in the second half of the year. Some heavy metals (Zn, Ni and Cu) were found to be at the lowest effect levels according to Ontario sediment quality guidelines. Additionally, most heavy metals were found to be at the non polluted level and level I according to USEPA sediment quality standards and National Institute of Environmental Research sediment pollution evaluation standard, respectively. The enrichment factor (< 1) and index of geoaccmulation (< 0) were non polluted in the study area. The correlation analysis results showed that ignition loss, total organic carbon and heavy metal content were highly correlated with grain size. Regarding changes in geochemical characteristics of surface sediments in the study area, grain size fine and organic matter and heavy metal content increased in the second half year. Nonetheless these results indicated pollution levels that did not adversely affect the benthos.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".