Wildfires threaten mercury stocks in northern soils, Geophys
Bibliographic record
Abstract
[1] With climate change rapidly affecting northern forests and wetlands, mercury reserves once protected in cold, wet soils are being exposed to burning, likely triggering large releases of mercury to the atmosphere. We quantify organic soil mercury stocks and burn areas across western, boreal Canada for use in fire emission models that explore controls of burn area, consumption severity, and fuel loading on atmospheric mercury emissions. Though renowned as hotspots for the accumulation of mercury and its transformation to the toxic methylmercury, boreal wetlands might soon transition to hotspots for atmospheric mercury emissions. Estimates of circumboreal mercury emissions from this study are 15-fold greater than estimates that do not account for mercury stored in peat soils. Ongoing and projected increases in boreal wildfire activity due to climate change will increase atmospheric mercury emissions, contributing to the anthropogenic alteration of the global mercury cycle and exacerbating mercury toxicities for northern food chains.). Citation: Turetsky,
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".