Autumn snowfall and hydroclimatic variability during the past millennium inferred from the varved sediments of meromictic Lake A, northern Ellesmere Island, Canada
Bibliographic record
Abstract
Abstract We examined the hydroclimatic signal in a record of annual lamina (varve) thickness from High Arctic Lake A, Ellesmere Island (83°00.00′N, 75°30.00′W). In this unglacierized catchment, nival melt is the dominant source for meltwater and transport of sediment to the lake, and autumn snowfall is highly influential on varve thickness through the amount of snow available for melt in the following year. For the period during which climatic data are available, varve thickness in Lake A was significantly correlated (r = 0.50, p < 0.01) with the cumulative snowfall from August to October (ASO) during the previous year and to a lesser extent, ASO mean daily temperature (r = 0.39, p < 0.01) at Alert, Nunavut (175 km east). The varve thickness record, interpreted as a proxy record of ASO snowfall and by extension, ASO temperature, indicated above-mean conditions during five periods of the past millennium, including most of the 20th century. These results corresponded well to other available high-resolution proxy climate records from the region, with some discrepancies prior to AD 1500 and during the period AD 1700–1900.
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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 | 0.001 | 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".