Current-Use and Legacy Pesticide History in the Austfonna Ice Cap, Svalbard, Norway
Bibliographic record
Abstract
The Svalbard archipelago in arctic Norway receives considerable semivolatile organic contaminant (SOC) inputs from the atmosphere. To measure the history of net SOC accumulation there, we analyzed the upper 40 m of an ice core from Austfonna, the largest ice cap in Eurasia, for several legacy organochlorine (OC) compounds and current-use pesticides (CUPs) including organophosphorus (OP), triazine, dinitroaniline, and chloroacetamide compounds. Five OP compounds (chlorpyrifos, terbufos, diazinon, methyl parathion, and fenitrothion), two OCs (methoxychlor and dieldrin), and metolachlor--an herbicide--had historical profiles in the core. The highest OC concentration observed was aldrin (69.0 ng L(-1)) in the surface sample (1992-1998). The most concentrated OP was dimethoate (87.0 ng L(-1)) between 1986 and 1992. The surface sample also had highest concentrations of pendimethalin (herbicide, 18.6 ng L(-1)) and flutriafol, the lone observed fungicide (9.6 ng L(-1)). The apparent atmospheric persistence of CUPs likely results from little or no oxidation by OH* during the dark polar winter and in spring. Long-range atmospheric pesticide transport to Svalbard from Eurasia is influenced by the positive state of the North Atlantic Oscillation Index since 1980 and also by occasional fast-moving summer air masses from northern Eurasian croplands.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".