Role of Snow Deposition of Perfluoroalkylated Substances at Coastal Livingston Island (Maritime Antarctica)
Bibliographic record
Abstract
Perfluoroalkyl substances (PFAS) are ubiquitous in the environment, including remote polar regions. To evaluate the role of snow deposition as an input of PFAS to Maritime Antarctica, fresh snow deposition, surface snow, streams from melted snow, coastal seawater, and plankton samples were collected over a three-month period (December 2014–February 2015) at Livingston Island. Local sources of PFASs were significant for perfluoroalkyl sulfonates (PFSAs) and C7–14 perfluoroalkyl carboxylates (PFCAs) in snow but limited to the transited areas of the research station. The concentrations of 14 ionizable PFAS (∑PFAS) in freshly deposited snow (760–3600 pg L –1 ) were 1 order of magnitude higher than those in background surface snow (82–430 pg L –1 ). ∑PFAS ranged from 94 to 420 pg L –1 in seawater and from 3.1 to 16 ng g dw –1 in plankton. Ratios of individual PFAS concentrations in freshly deposited snow relative to surface snow ( C SD / C Snow ), snowmelt ( C SD / C SM ), and seawater ( C SD / C SW ) were close to 1 (from 0.44 to 1.4) for all perfluorooctanesulfonate (PFOS) isomers, suggesting that snowfall does not contribute significantly to PFOS in seawater. Conversely, these ratios for PFCAs ranged from 1 to 33 and were positively correlated with the number of carbons in the PFCA alkylated chain. These trends suggest that snow deposition, scavenging sea-salt aerosol bound PFAS, plays a role as a significant input of PFCAs to the Maritime Antarctica.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".