Inferring sources for mercury to inland lakes using sediment chronologies of polycyclic aromatic hydrocarbons
Bibliographic record
Abstract
Sediment chronologies from inland lakes suggest the influence of local to sub-regional scale sources for mercury (Hg). However, apportionment of sources for Hg using sediment chronologies is difficult due to the mixing of sources and pathways. Mercury and polycyclic aromatic hydrocarbons (PAH) often share common sources and pathways into the environment. Thus, chronologies of PAHs in dated cores of sediments might be a useful tool to infer sources of Hg. Sediment cores from seven inland lakes of Michigan were collected for measurement of PAHs and Hg and dated by use of (210)Pb. PAH concentrations and ratios of kinetic and thermodynamic PAH compounds were used to infer sources of Hg. Ratios indicate the existence of modern combustion sources to each lake and historic combustion sources to lakes near cement kilns and an iron foundry. Coal combustion sources were identified for two lakes near urban centers. Whereas a petroleum combustion source was identified for a lake that has a coal fired power plant along its shoreline. These results have implications for the cycling of Hg on local to regional scales.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".