HEAVY METAL ANALYSIS OF THE GEDIZ RIVER, TURKEY
Bibliographic record
Abstract
This paper drives the mathematical discussion of heavy metals level of As, Pb, Cd, Ni, Cu, Co and Cr in the samples collected from the Gediz Delta. In 2006, several scientists from Ege University Faculty of Fisheries declared the data of eight different stations belonging to the basin to observe the natural and anthropogenic effect in the sediment of the delta. Based on these data, we try to look at the results with a more comprehensive mathematical perspective and attract the attention to the Gediz Basin with holistic discussions. Land use in the watershed and a data set comprised of observations of 7 heavy metals from 8 locations are described. In order to interpret the anthropogenic effect of contamination of the river, statistical analyses are performed. In the study, by investigation a covariance matrix indicates the strength of bivariate relationships, a dendrogram shows hierarchical clustering into different groups, and factor analysis indicates three distinct eigenvectors. In addition, one can find three indices Contamination Factor (CF), Enrichment Factor (EF), and Pollution Load Index (PLI) developed by Canadian sedimentologists. The fact that the findings in the discussion belong to 2006 permits the authors to understand the recent condition more clearly. The level of pollution from the past is comparable.
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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 | 0.002 | 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) | 0.000 | 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 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".