Scavenging Amphipods: Sentinels for Penetration of Mercury and Persistent Organic Chemicals into Food Webs of the Deep Arctic Ocean
Bibliographic record
Abstract
Archived specimens of the scavenging amphipod Eurythenes gryllus, collected from 2075 to 4250 m below the surface on five expeditions to the western and central Arctic Ocean between 1983 and 1998, were analyzed for total mercury (∑Hg), methyl mercury (MeHg), polychlorinated biphenyls (PCBs) and other industrial or byproduct organochlorines (chlorobenzenes, pentachloroanisole, octachlorostyrene), organochlorine pesticides (OCPs), and polybrominated diphenyl ethers (PBDEs). Median ∑Hg concentrations ranged from 70 to 366 ng g(-1) wet weight (ww). MeHg concentrations (3.55 to 23.5 ng g(-1) ww) accounted for 1.7 to 20.1% (median 3.7%) of ∑Hg. ∑Hg and MeHg were positively and significantly correlated with ww (∑Hg r(2) = 0.18, p = 0.0004, n = 63; MeHg r(2) = 0.42, p = 0.0004, n = 25), but not significantly with δ(13)C nor δ(15)N. Median concentrations of total persistent organic pollutants (POPs) ranged from 9750 to 156,000 ng g(-1) lipid weight, with order of abundance: ∑TOX (chlorobornanes quantified as technical toxaphene) > ∑PCBs > ∑DDTs > ∑chlordanes > ∑mirex compounds > ∑BDEs ∼ ∑chlorobenzenes ∼ octachlorostyrene > α-hexachlorocyclohexane ∼ hexachlorobenzene ∼ pentachloroanisole. Enantioselective accumulation was found for the chiral OCPs o,p'-DDT, cis- and trans-chlordane, nonachlor MC6 and oxychlordane. Lipid-normalized POPs concentrations were elevated in amphipods with lipid percentages ≤10%, suggesting that utilization of lipids resulted in concentration of POPs in the remaining lipid pool. Multidimensional Scaling (MDS) analysis using log-transformed physiological variables and lipid-normalized organochlorine concentrations distinguished amphipods from the central vs western arctic stations. This distinction was also seen for PCB homologues, whereas profiles of other compound classes were more related to specific stations rather than central-west differences.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".