Abstract: A multi-proxy study on decadal to centennial timescale variations in freshwater discharge recorded in the marine sedimentary record of the Nelson River estuary (Manitoba) and offshore of the Great Whale River mouth (Quebec) in Hudson Bay (poster presentation)
Bibliographic record
Abstract
This study aims to bring recent variations in river water discharge into the Hudson Bay Basin into an appropriate centennial to millennial climatic context by studying the marine sedimentary record. This will help to distinguish between natural variability and possible anthropogenic impacts due to global warming. The marine sedimentary record of two field localities, the Nelson River estuary (western coast of Hudson Bay) and a sedimentary basin offshore of the Great Whale River mouth (eastern coast of Hudson Bay), will be used to study river water and sediment discharge, marine sediment dispersal and accumulation processes and the history of river runoff variations in Hudson Bay. Recent observations in river discharge from the Canadian Shield to the Canadian sub-Arctic/ Arctic show large variations during the past forty years. These variations have a substantial influence on the marine ecosystem and on sea-surface conditions and deep water formation in the Labrador Sea and thus on the global thermohaline circulation. There is a critical need to increase our understanding of paleo-river-discharge variations to place our current knowledge in a longer climatological context and to prepare for possible future changes. The study applies a multi-proxy approach to
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".