Controls on the <sup>14</sup>C Content of Dissolved and Particulate Organic Carbon Mobilized Across the Mackenzie River Basin, Canada
Bibliographic record
Abstract
Abstract The Mackenzie River Basin (MRB) delivers large quantities of organic carbon (OC) into the Arctic Ocean, with significant implications for the global C budgets and ocean biogeochemistry. The amount and properties of OC in the Mackenzie River's delta have been well monitored in the last decade, but the spatial variability in OC sources transported by its different tributaries is still unclear. Here we present new data on the radiocarbon (14C) content of dissolved and particulate OC (Δ14C‐DOC and Δ14C‐POC) across the mainstem and major tributaries of the MRB, comprising 19 different locations, to identify factors controlling spatial patterns in riverine OC sources. The Δ14C‐DOC and Δ14C‐POC varied across a large range, from −179.9‰ to 62.9‰, and −728.8‰ to −9.0‰, respectively. Our data reveal a positive spatial coupling between the Δ14C of DOC and POC across the MRB, whereby the most 14C‐depleted waters were issued from the mountainous west bank of the MRB. This 14C‐depleted DOC and POC likely originates from a combination of petrogenic sources, connected with the presence of kerogens in the bedrock, and biogenic sources, mobilized by thawing permafrost. Our analysis also reveals intriguing relationships between Δ14C of DOC and POC with turbidity, water stable isotope ratio and catchment elevation, indicating that hydrology and geomorphology are key to understanding riverine OC sources in this landscape. A closer examination of the specific mechanisms giving rise to these relationships is recommended. For now, this study provides a road map of the key OC sources in this rapidly changing river 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".