Sources and Evolution of Anthropogenic Lead in Dated Sediments from Lake Clair, Québec, Canada
Bibliographic record
Abstract
Two sediments cores were collected from the deepest part of Lake Clair (Québec, Canada) to assess the historical sources of Pb additions to the lake. The cores were collected by divers by carefully inserting a Plexiglas tube into the sediments. To determine the stratigraphic ages of the sediments, (210)Pb and (137)Cs activities were counted by gamma-ray spectroscopy. Lead concentrations and isotopic ratios were performed by inductively coupled plasma-mass spectrometry (ICP-MS), following digestion of the samples with a mixture of HF, HNO(3), and HClO(4) acids and Pb separation by anion-exchange chromatography. Starting at the middle of the 19th century, Pb content of the sediments increased until 1975. The maximum Pb enrichment factor of 35 times (relative to the natural background) was found in sediments deposited in 1975. At this time, excess Pb flux was estimated to be about 0.03 g m(-2) yr(-1). Before 1872, the Pb isotopic ratios were relatively stable (mean (206)Pb/(207)Pb = 1.20 +/- 0.01), reflecting the natural Pb background. Between 1872 and 1894, the source of anthropogenic Pb was highly radiogenic as shown by the Pb isotopic signatures of the sediments (mean (206)Pb/(207)Pb = 1.22 +/- 0.01), possibly reflecting deforestation and agricultural developments in the St.-Lawrence Valley. Between 1894 and 1937, widespread use of industrial and domestic charcoals may explain the isotopic composition of Pb accumulated in the sediments (mean (206)Pb/(207)Pb = 1.19 +/- 0.01). From 1937 to 1975, Pb isotopic compositions became less radiogenic ((206)Pb/(207)Pb from 1.18 to 1.17) even though elemental Pb abundance reached extremely high values (623 mg kg(-1)). This isotopic shift reflects increased use of alkyl-lead in gasoline. For sediments accumulated between 1967 and 1996, the U.S. contribution to anthropogenic Pb accumulated in Lake Clair sediments amounted to between 30 and 63%.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".