Determination of particulate organic carbon sources to the surface mixed layer of the Canada Basin, Arctic Ocean
Bibliographic record
Abstract
Abstract Stable isotope ratios of particulate organic carbon (POC), together with other tracers, were analyzed in samples from the Canada Basin surface mixed layer in 2008 and 2009. Sampling was conducted during the end of the 2008 melt season and at the beginning of the 2009 freezeup under a variety of surface conditions, including open water, newly formed seasonal ice, and multiyear ice. In both years, POC exhibited a wide isotopic range (δ13C‐POC −24.5 to −31.1‰), with the most isotopically depleted material generally found in the central basin. Isotopically enriched material was found on the shelves, consistent with higher biological production and strongly correlated with in situ carbon‐uptake rates. In contrast, offshore in the central basin, there was no significant relationship between δ13C‐POC distributions and either chlorophyll a or aqueous CO2 concentrations, suggesting that in situ biological production was not the dominant control. Analysis of freshwater sources suggested that the sea ice melt contribution of POC to surface waters in the central Canada Basin exerted a negligible influence on δ13C‐POC distributions, and instead isotopically depleted POC in the surface waters of the central Canada Basin were sourced externally through advective transport of riverine organic matter. We show that alkalinity and meteoric water content can be used to distinguish POC inputs from North American and Russian rivers and our analysis suggests that Russian river inputs are the predominant source of 13C‐depleted organic matter to the mixed layer of the central Canada Basin.
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) | 0.001 | 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) | 0.000 | 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".