Regionale und substratabhängige Verteilung von Schwermetallen in oberflächennahen Sedimenten des Inner Kingston Basin, Ontariosee
Bibliographic record
Abstract
The sequential extraction scheme BCR 701 has been applied to the upper 2 cm layer of 39 sediment samples from Inner Kingston Basin, Ontario. The samples were also been characterized by water content, loss on ignition at 550°C and 950°C and by particle size distribution. Methodological problems occurred during particle size analysis, caused by agglomerating effects, mainly driven by organic matter, which is fairly resistant against oxidation by hydrogen peroxide due to natural manganese dioxide particles in the sediments. This leads to an overestimation of the clay content. For the same reason, the digestion in step 3 of the sequential extraction was insufficient, so that typical organic bound metals were found in the residual fraction. From factor and cluster analysis of all data three main substrate element associations were derived: The carbonate group contains Ca, Sr, LOI 950°C from calcite, and in step 2 additional Mg extracted from dolomite. Secondly, the organic associations include LOI 550°C, water content and clay content, and finally the metals (except from carbonate bound metals) which are more or less linked to the organic associations. Regionalized maps using inverse distance weighting or ordinary Kriging have been judged to be less precise and informative than point data maps using a classification following equal standard deviation distances and additional statistical information, box plots and histograms. Compared to the geogenic background, all samples show a significant metal enrichment in the mobile fractions, so that they could easily be remobilized during changing environmental conditions. Higher enrichment rates have been detected around the city of Kingston, mainly the harbour region, and close to the outlet of Kingston s sewage treatment plant. Generally, local contamination can easily be detected and differentiated according to their origin from sequential extraction data.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".