Iceberg production and characteristics around the Prince of Wales Icefield, Ellesmere Island, 1997-2015
Bibliographic record
Abstract
Since the 1960s, warming air and sea surface temperatures have led to decreasing sea ice extent and longer periods of open water in the Canadian Arctic Archipelago (CAA), together with changes in glacier discharge patterns. An important question, therefore, is whether there is a relationship between changing sea ice conditions, glacier dynamics, and iceberg production in this region. Using synthetic aperture radar (SAR) (Radarsat-1, Radarsat-2, and ALOS PALSAR) and optical (Landsat 7 and 8) satellite imagery, iceberg plume events and sea ice break-up/freeze-up dates between 1997 and 2015 are investigated for 40 tidewater glaciers around the Prince of Wales (POW) Icefield, Ellesmere Island. Results show a clear relationship between the presence of sea ice and the production of icebergs, with ~49% of total iceberg plume events occurring during the 3–4 month long summer open water season and ~51% of events when sea ice was present the remaining 8–9 months of the year. There is no clear evidence of recent increases in iceberg production on a regional basis, but on a local, individual glacier scale there has been a connection between periods of increased iceberg plume events and: (a) acceleration in the surface velocity of Trinity and Wykeham glaciers; (b) increase in terminus retreat rates for glaciers which have not accelerated in flow speed over the past ~5–10 years. Comparisons with ocean temperature, surface air temperature from NCEP-NCAR reanalysis, and tidal data showed no clear relationship with iceberg plume events.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".