Thirty‐seven year mass balance of Devon Ice Cap, Nunavut, Canada, determined by shallow ice coring and melt modeling
Bibliographic record
Abstract
In April–May 2000, eight boreholes were drilled to ∼15–20 m depth on the Devon Ice Cap. 137Cs γ activity profiles of each borehole showed a peak count rate at depth that is associated with fallout from atmospheric thermonuclear weapons testing in 1963. Snow, firn, and ice densities were measured at each core site and were used to estimate the average pattern of mass balance across the accumulation zone of the ice cap over the period 1963–2000. The average mass balance across the entire ice cap for the period 1960–2000 was also estimated using a degree‐day model driven by data derived from on‐ice temperature sensors and long‐term measurements at Resolute Bay. Best fitting degree‐day factors were determined for different sectors of the ice cap by comparing model output with repeated annual mass balance measurements made along two transects (Koerner, 1970). The results suggest that the ice cap has lost ∼1.6 km3 water per year, equivalent to a mean net mass balance of approximately −0.13 m We a−1. Estimates of the mean mass balance for individual drainage basins reveal regions of positive and negative mass balance that are consistent with remotely sensed observations of advancing and retreating ice cap margins, respectively.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".