Iron and humic‐type fluorescent dissolved organic matter in the Chukchi Sea and Canada Basin of the western Arctic Ocean
Bibliographic record
Abstract
The concentrations of dissolved Fe ([D‐Fe]), total dissolvable Fe ([T‐Fe]), humic‐type fluorescence intensity (humic F intensity) as humic‐type fluorescent dissolved organic matter, and nutrients were vertically determined in the shelf, slope, and basin regions (Chukchi Sea and Canada Basin) of the western Arctic Ocean during 1–27 September 2008. In all stations, the remarkably high [D‐Fe] and humic F intensity were found at depths between 25 and 200 m with the subsurface maxima of [D‐Fe] (1.0–3.2 nM) and humic F intensity (4–5 quinine sulfate units) in the upper halocline layer (upper HL), being associated with a prominent nutrient maximum. The high [D‐Fe] and humic F intensity within the upper HL are probably attributed to the Fe(III) complexation with natural organic ligands, such as marine dissolved humic substances, resulting from main processes of the brine rejection during sea ice formation and interactions with sediments on the shelves. However, subsurface maxima (10–50 nM) of [T‐Fe] were found in the lower halocline layer, beneath the upper HL, of all slope and basin regions and are mainly attributed to the resuspension of sedimentary particles in the shelf region. The finding of subsurface iron maxima in the halocline water of all regions may be the first confirmation for the lateral iron transport into the halocline layer from the shelves to the Arctic Basin.
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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 | 0.002 |
| 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) | 0.000 | 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".