Use of Stable Isotope Signatures to Determine Mercury Sources in the Great Lakes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Sources of mercury (Hg) in Great Lakes sediments were assessed with stable Hg isotope ratios using multicollector inductively coupled plasma mass spectrometry. An isotopic mixing model based on mass-dependent (MDF) and mass-independent fractionation (MIF) (δ 202 Hg and Δ 199 Hg) identified three primary Hg sources for sediments: atmospheric, industrial, and watershed-derived. Results indicate atmospheric sources dominate in Lakes Huron, Superior, and Michigan sediments while watershed-derived and industrial sources dominate in Lakes Erie and Ontario sediments. Anomalous Δ 200 Hg signatures, also apparent in sediments, provided independent validation of the model. Comparison of Δ 200 Hg signatures in predatory fish from three lakes reveals that bioaccumulated Hg is more isotopically similar to atmospherically derived Hg than a lake’s sediment. Previous research suggests Δ 200 Hg is conserved during biogeochemical processing and odd mass-independent fractionation (MIF) is conserved during metabolic processing, so it is suspected even is similarly conserved. Given these assumptions, our data suggest that in some cases, atmospherically derived Hg may be a more important source of MeHg to higher trophic levels than legacy sediments in the Great Lakes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it