Patterns and mechanisms of fluvial sediment flux and accumulation in two subarctic fjords: Nachvak and Saglek Fjords, Nunatsiavut, Canada
Bibliographic record
Abstract
Recent marine sedimentary deposits and river discharge in two subarctic fjords in Nunatsiavut (Northern Labrador, Canada) have been studied to elucidate patterns and mechanisms of fluvial sediment transfer and accumulation in the fjords, to further our understanding of the longer-term sedimentary record. Multibeam and sub-bottom acoustic data and sediment cores were collected in Nachvak and Saglek fjords, within Canada’s Torngat Mountains National Park, as part of the most extensive study of the park’s marine resources to date. Cores were subsampled for X-radiography, grain size, and 210Pb/137Cs geochronology. Muddy basin sediments within each fjord are bioturbated, indicating circulation of oxygenated bottom water. Depositional fluxes and inventories of 210Pb indicate efficient marine scavenging of 210Pb by fine suspended sediments. In Nachvak Fjord, with small rivers and steep, presently glaciated catchments, postglacial and recent sediment accumulation rates are similar, implying relatively constant sedimentation over time. In Saglek Fjord, fed by larger rivers with more extensive catchments that lack glaciers, recent sediment accumulation is more rapid than that averaged over postglacial time. Present mass accumulation rates for the Nachvak Fjord basin are on average 39 000 t·year–1 for the entire basin, and for Saglek 43 000 t·year–1 for the entire basin, with sediment-gravity flows being one likely mechanism for sediment delivery to deep basins. Results collectively suggest that both marine basins are excellent natural sediment traps. Comparison of accumulation rates from 137Cs and 210Pb suggest that sediment fluxes to Nachvak Fjord may have decreased slightly over the past ∼130 years.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".