<i>Sphagnum</i>Mosses from 21 Ombrotrophic Bogs in the Athabasca Bituminous Sands Region Show No Significant Atmospheric Contamination of “Heavy Metals”
Bibliographic record
Abstract
Sphagnum moss was collected from 21 ombrotrophic (rain-fed) peat bogs surrounding open pit mines and upgrading facilities of Athabasca bituminous sands in Alberta (AB). In comparison to contemporary Sphagnum moss from four bogs in rural locations of southern Germany (DE), the AB mosses yielded lower concentrations of Ag, Cd, Ni, Pb, Sb, and Tl, similar concentrations of Mo, but greater concentrations of Ba, Th, and V. Except for V, in comparison to the "cleanest", ancient peat samples ever tested from the northern hemisphere (ca. 6000-9000 years old), the concentrations of each of these metals in the AB mosses are within a factor of 3 of "natural, background" values. The concentrations of "heavy metals" in the mosses, however, are proportional to the concentration of Th (a conservative, lithophile element) and, therefore, contributed to the plants primarily in the form of mineral dust particles. Vanadium, the single most abundant trace metal in bitumen, is the only anomaly: in the AB mosses, V exceeds that of ancient peat by a factor of 6; it is therefore enriched in the mosses, relative to Th, by a factor of 2. In comparison to the surface layer of peat cores collected in recent years from across Canada, from British Columbia to New Brunswick, the Pb concentrations in the mosses from AB are far lower.
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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".