Development, evolution and drainage of glacial Lake Naskaupi during the deglaciation of north‐central Quebec and Labrador
Bibliographic record
Abstract
ABSTRACT Deglaciation of north‐central Quebec and Labrador led to the development of large ice‐dammed lakes in river valleys surrounding Ungava Bay. These lakes are poorly understood due to uncertainties in the regional pattern of ice retreat. Lake Naskaupi occupied the George River valley where systematic mapping of glacial landforms and extensive elevation measurements of shorelines reveal a complex history characterized by multiple lake levels. Our reconstruction documents three well‐defined lake levels marking extensive lake stages. Additional lake levels are poorly developed and relate to short‐lived, transient lake stages. During its main stage (N2′), Lake Naskaupi consisted of two separate basins that evolved independently for some time. This configuration resulted from the persistence of cold‐based ice conditions during the deglaciation that caused the retreating ice margin to remain in the middle section of the river valley. The presence of this ice dam is supported by large‐scale outburst flood deposits that record the abrupt drainage of the southern Naskaupi basin. The magnitude of the elevation changes between the remaining lower lake levels suggests the occurrence of at least one other major drawdown before the final lake drainage. Reconstruction of the N2′ lake stage provides a minimum meltwater volume estimate for the lake.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".