Reconnaissance Study of Selected Trace Metal Concentrations In Sediments and Vegetation of the Yukon-Kuskokwim Delta Submitted by Mary Yunak-Martinez
Bibliographic record
Abstract
To establish a biogeochemical baseline in the Yukon-Kuskokwim Delta (Y-K Delta) region for future environmental studies, trace metal concentrations were determined for stream sediment and vegetation samples. Selected trace metal concentrations in vegetation samples were compared to the same metal content in stream sediment samples to determine whether a correlation between plant chemistry and the underlying geology exists, whether variations in metal concentrations in sediment and vegetation samples between geographic quadrants exist and to ascertain the element concentrations by plant types. Spearman’s rank order correlation was applied to statistically determine the presence, or absence, of correlation of selected metal concentrations of arsenic, mercury, lead, selenium and zinc. The strength of significance of the results was based on a p value of 0.05 (where p is the probability of rejecting a true null hypothesis). The null hypothesis for this study is that there is no relationship between metal concentrations in vegetation and that in the sediment. When p is < 0.05, the null hypothesis is rejected, indicating correlation between the parameters. Therefore, as p approaches 0, correlation between sediment and
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".