The mercury isotope composition of Arctic coastal seawater
Bibliographic record
Abstract
For the first time, Hg isotope composition of seawater in the Canadian Arctic Archipelago is reported. Hg was pre-concentrated from large volumes of seawater sampling using anion exchange resins onboard the research vessel immediately after collection. Elution of Hg was performed in laboratory followed by isotope composition determination by multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). For comparison, seawater from two stations was shipped to the laboratory and processed within it. Results showed negative mass-dependent fractionation in the range from –2.85 to –1.10‰ for δ 202 Hg, as well as slightly positive mass-independent fractionation of odd Hg isotopes. Positive mass-independent fractionation of 200 Hg was also observed. Samples that were pre-concentrated in the laboratory showed different Hg isotope signatures and this is most probably due to the abiotic reduction of Hg in the dark by organic matter during storage and shipment after sampling. This emphasizes the need for immediate onboard pre-concentration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".