The role of decomposing plant litter in methylmercury cycling in a boreal poor fen /
Bibliographic record
Abstract
Decomposition and MeHg concentration were measured for Sphagnum fuscum, Sphagnum angustifolium and Chamaedaphne calyculata in a poor fen in the low boreal forest zone of the Canadian Shield. Litter bags were transplanted reciprocally into hummocks, hollows and lawns and retrieved after 1, 2, 3,11 and 15 months. Mass losses follow the trend: Chamaedaphne calyculata >> S. angustifolium > S. fuscum. Between species differences were far more significant than differences between locations or depths, indicating that litter quality is the major control on decomposition. McHg concentrations generally increased during decomposition, particularly near the water table: for C. calyculata up to 13000%, for the two Sphagnum mosses up to 500%, suggesting that decomposition stimulates mercury methylation or McHg scavenging. The discovery of a high McHg substance on C. calyculata leaf surfaces (25 ng g-1) suggests that much plant MeHg data may by skewed by the presence of a biologically active 'film'.
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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 | 0.000 | 0.000 |
| 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".