Insights Into Water Mass Origins in the Central Arctic Ocean From In‐Situ Dissolved Organic Matter Fluorescence
Bibliographic record
Abstract
Abstract The Arctic Ocean receives a large supply of dissolved organic matter (DOM) from its catchment and shelf sediments, which can be traced across much of the basin's upper waters. This signature can potentially be used as a tracer. On the shelf, the combination of river discharge and sea‐ice formation, modifies water densities and mixing considerably. These waters are a source of the halocline layer that covers much of the Arctic Ocean, but also contain elevated levels of DOM. Here we demonstrate how this can be used as a supplementary tracer and contribute to evaluating ocean circulation in the Arctic. A fraction of the organic compounds that DOM consists of fluoresce and can be measured using in‐situ fluorometers. When deployed on autonomous platforms these provide high temporal and spatial resolution measurements over long periods. The results of an analysis of data derived from several Ice Tethered Profilers (ITPs) offer a unique spatial coverage of the distribution of DOM in the surface 800 m below Arctic sea‐ice. Water mass analysis using temperature, salinity and DOM fluorescence, can clearly distinguish between the contribution of Siberian terrestrial DOM and marine DOM from the Chukchi shelf to the waters of the halocline. The findings offer a new approach to trace the distribution of Pacific waters and its export from the Arctic Ocean. Our results indicate the potential to extend the approach to separate freshwater contributions from, sea‐ice melt, riverine discharge and the Pacific Ocean.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".