Application of a Sediment Quality Index to the Masan Bay, Korea
Bibliographic record
Abstract
A sediment quality index (SQI) and a mean sediment quality guideline quotient (M-SQGQ) were applied for the assessment of sediment quality in Masan Bay, Korea where metals and organic pollutants are of concern. The SQI was calculated by two functions, 'scope' (the number of variables that do not meet guideline objective) and 'amplitude' (the magnitude by which variables exceed guideline objective), with six different sediment quality guideline values from Canada, USA and Australia/New Zealand. Categorization of sediment quality was on the basis of SQI scores. The SQI values were compared with six guideline values applied as well as with the M-SQGQs. The SQI values were severely influenced by a few variables of high exceedance in the degree of non-compliance. The SQI values were very dependent on both the numbers and values of guideline variables used in index caluculation. Nevertheless, the SQI could provide integrated and simplified information from a large number of chemical data set. It is required to further evaluate protocols and guideline applied for deriving SQI and to compare it with field based sediment toxicity test and ecosystem integrity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.000 | 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 teacher head, 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".