Dissolved organic matter (DOM) and barium in James Bay: Distribution, sources, and climate change implications
Bibliographic record
Abstract
The properties of dissolved organic matter (DOM) were examined in a dataset representative of the James Bay (Canada) marine system following two summer expeditions in 2021 and 2022. The absorption coefficients at 275 nm (a 275 ) and 295 nm (a 295 ) of the chromophoric DOM (CDOM) were used to establish a region-specific, usable in-depth, predictive model of dissolved organic carbon (DOC) concentration in summer, with a mean absolute percentage error of only 11 %, comparable to other models in polar environments. The DOC concentration, a 350 , the spectral slope between 275 and 295 nm (S 275–295 ), the dissolved barium concentration, and four PARAFAC components (three humic-like and one protein-like) were employed as freshwater tracers. At the surface, we observed a very low DOM region in the north-west of the bay associated with the inflow of marine waters from Hudson Bay, a highly DOM-rich region in the south and east in James Bay caused by strong riverine inputs and, in the north-east, a very fresh region, but with lower DOM concentrations than to the south, induced by the discharge of the La Grande River. At depth, a homogeneous, low DOM distribution is observed in the north of James Bay, extending from east to west. In contrast, the deep water to the south is much richer in DOM and appears to circulate along the east coast. The lack of exchange at depth between the northern and southern regions is attributed to the presence of a sill that creates a physical barrier. The analysis of lignin-phenols in surface samples revealed a more “woody gymnosperm” vegetation compared to the Hudson Bay Rivers further north, which is in line with the known vegetation surrounding the Bay. The portrait of the DOM in offshore James Bay in summer thus provides a benchmark for studying the evolution of the carbon pool under climate change in this region, which is likely to undergo significant upheaval due to permafrost thaw, increased riverine inputs, and alteration of the vegetal ecosystem.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".