Historical variation of elements with respect to different geochemical fractions in recent sediments from Pigeon Lake, Alberta, Canada
Bibliographic record
Abstract
Geochemical analysis of elements and organic matter were conducted on vertical profiles of the recent sediments from Pigeon Lake, Alberta, Canada, to determine historical variations in elemental content of the sediments as related to their geochemical fractions. The elements are grouped according to their affinity with different geochemical fractions, by using cluster analysis and sequential extraction experiments. As a result, four elemental fractions were identified: clastic mineral detritus; carbonate; organic; and elements that show less similarity to the previous groups perhaps due to anthropogenic input or the influence of other fractions, such as oxyhydroxides. Following the identification of geochemical fractions in the sediments, a three-step normalizing method was applied using parameters that represent each geochemical fraction. These normalizing techniques appear to be important in verifying whether the variation of elements is indeed the result of anthropogenic and/or natural activities. The normalized data are correlated with the recent history of human activity and natural events near Pigeon Lake. Given the age of the lake sediments, this correlation indicates that the depth profiles of elements after being normalized to the organic and carbonate fractions reflect the variation of detrital input into the lake. However, the former mainly corresponds to the coarse-grained clastic minerals originating from high-energy erosion as the result of natural events (e.g., flooding), whereas the latter corresponds to the low-energy erosion of the fine particles (enriched in lithophile elements) due to deforestation in the drainage basin. Normalizing to the clastic mineral detritus fraction results in the increase of heavy metals in the uppermost part of the sediment profiles, which coincides with industrial activities during the past two decades in central Alberta. However, the concentration of these elements is negligible, as compared to the quantities released by geogenic processes (erosion).
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".