Early Holocene glacial lake meltwater injections into the Labrador Sea and Ungava Bay
Bibliographic record
Abstract
In this paper we analyze drainage routes and estimate fluxes of meltwater released from Labrador‐Ungava glacial lakes into the Labrador Sea, Ungava Bay, and Hudson Bay between 7.5 and 6.0 kyr BP (8.4–7.0 calendar (cal) years ka). The analysis and estimates are based on landform‐based reconstructions of the Laurentide Ice Sheet (LIS) decay pattern and the associated glacial lake evolution. Geomorphological data constraining the spatial extent of glacial lakes are coupled to a digital terrain model for meltwater volume calculations. The LIS ice recession between 7.5 and 6.0 kyr BP led to the formation of a large number of glacial lakes, which drained in approximately 30 meltwater pulses, with fluxes exceeding 0.015 Sv (1 Sv = 106 m3 s−1), into Labrador Sea, Ungava Bay, and Hudson Bay. The inferred rapid ice margin retreat during late stages of deglaciation indicates that these drainage events were relatively short‐lived. The early Holocene glacial lakes of Labrador‐Ungava released meltwater, resulting in a total inflow of ∼6000 km3 freshwater to the North Atlantic. The pulsed nature of meltwater release from the lakes is likely to have resulted in rapid repeated cooling of the Labrador Sea surface water.
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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 | 0.000 | 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".