Long-term field tracking of icebergs in the eastern Canadian Arctic
Bibliographic record
Abstract
Tidewater glaciers are those which terminate into the ocean and drain a significant proportion of the Greenland Ice Sheet and ice masses of the Canadian Arctic, providing the primary source of icebergs in Canadian waters. Once calved, there remains uncertainty concerning the processes controlling their drift. This study uses a multi-year dataset (2011–2019) of in situ iceberg observations to characterize drift on a regional scale throughout Baffin Bay. We identify common grounding areas and quantify the influence of wind, ocean, and tidal currents using ERA5 climate reanalysis, global ocean reanalysis and simulations, and WebTide Tidal Prediction models. Icebergs in the Eastern Canadian Arctic consistently drifted southeast along the east coast of Baffin Island. We evaluate the assumption that icebergs drift at 2% of the wind speed and determine that this rule does not apply for the majority of icebergs in this study, which often exceeded 2% of the wind speed, in particular at low wind speeds. The highest speeds occurred during the winter and spring, reaching up to 2.3 m s−1 in Nares Strait. Our analysis indicates that iceberg drift patterns are controlled by a combination of local conditions including short-term wind events, ocean surface currents, and semi-diurnal tidal oscillations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".