Insights into the Global Distribution of Polychlorinated Dibenzo-<i>p</i>-dioxins and Dibenzofurans
Bibliographic record
Abstract
Polychlorinated dibenzo- p -dioxins and dibenzofurans were measured in 63 pairs of tree bark and soil samples. Maps of lipid-adjusted concentrations in bark and fluxes to soil indicated that Vancouver Island, the Midwestern United States, Germany, and Hong Kong were areas of high PCDD/F deposition. Concentrations and fluxes in the regions north of the 60th parallel, particularly the Canadian Arctic, were low, indicating that PCDD/F do not move appreciably from warm to cold latitudes. Linear regressions of the PCDD/F concentrations in tree bark versus fluxes to soil showed that total concentrations in bark can be used to estimate total fluxes to soil in a particular region. Comparison of the homologue profiles for each pair of bark and soil samples indicated that the pairs fell into three categories: 1. bark and soil both resembled source profiles; 2. bark and soil both resembled sink profiles; and 3. bark resembled a source profile but the soil resembled a sink profile. This variation in homologue profiles may be due to the proximity of sampling locations to sources. We found that anthropogenic NO x emissions are highly correlated to PCDD/F soil fluxes, and we used this regression to estimate global PCDD/F fluxes to soil on the same spatial scale as the NO x data. Multiplying these fluxes by the corresponding land areas, we estimated that total PCDD/F deposition to the earth's land surface is about 2−15 t/yr.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".