The Calving Events of Petermann Glacier From 2008 to 2012: Ice Island Drift Characteristics, Assessment of Fracture Events, and Geographical Data Analysis
Bibliographic record
Abstract
Abstract The eastern Canadian Arctic is an ice-prone environment that is a vital part of Canadian Arctic shipping lanes. A better understanding of the ice environment and ice characteristics in this region is essential for supporting safe and economical marine activities. This study presents a first analysis of the drift of ice islands that originated from the Petermann Glacier calving events in northwest Greenland between 2008 and 2012. These massive calving events generated numerous smaller ice islands and icebergs through subsequent deterioration and break-up events. Surviving ice features drifted further southward into the Baffin Bay and reached as far as offshore Newfoundland (∼47 °N) for the case of the 2010 calving event. The drift characteristics of Petermann ice islands are evaluated through the analysis of the recently developed Canadian Ice Island Drift, Deterioration and Detection (CI2D3) database. The average drift distance, speed, and directions of the ice islands that resulted from the 2008, 2010, and 2012 calving events were estimated using successive observations of the monitored ice islands in the CI2D3 database. This study also includes an assessment of fracture events, including the total number of ice island break-up events following each massive calving event and the average number of daughter ice islands resulting from each break-up event. A geographical analysis of the data was also performed to present the location of the fracture events, as well as the time series of latitude change of Petermann ice islands from their origin (northwest Greenland ice tongues) to where until they became too small (< 0.25 km2) to be delineated in the CI2D3 database. This information is of particular interest to marine activities in the eastern Canadian Arctic, and oil and gas operations offshore Newfoundland and Labrador.
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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 | 0.004 | 0.004 |
| 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".