Modeling Evidence of Episodic Intercontinental Long-Range Transport of Lindane
Bibliographic record
Abstract
Two global atmospheric transport models for persistent toxic substances were employed to quantify the intercontinental atmospheric transport of lindane in 2005 using a recently constructed global lindane emission inventory. The focus of this numerical investigation was to identify, on an intercontinental scale, the major sources of lindane that contributed to the contamination of North America and the Arctic. Both models simulated several strong episodic trans-Pacific atmospheric transport events of lindane from its sources in Asia to the western seaboard of North America. Modeling results also detected, forthe firsttime, an important atmospheric pathway for persistent toxic substances from Western Africa/Western Europe to the Caribbean, the southern United States, and the eastern seaboard of North America. Several episodic lindane transAtlantic atmospheric transport events were found from May to October. These events were associated primarily with the easterly trade winds and the African easterly wave that extends from the subtropical eastern Atlantic to the Caribbean. This atmospheric pathway for toxic chemicals has a substantial implication for the level of toxic substances in North America. Atmospheric mechanisms contributing to these transport events are briefly discussed. Multiple modeling scenarios were studied to assess the contribution of lindane sources in Europe, Asia, and North America to its fate in the Arctic. Results show that these continental contributions are season-dependent with the highest contribution from Europe in the spring.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".