A statistical analysis of landfast sea ice breakout events at the northern floe edge of Admiralty Inlet, Nunavut
Bibliographic record
Abstract
In the spring, Inuit travel across landfast ice to the northern floe edge in Admiralty Inlet to hunt.During this time, the floe edge can be unstable, and floes can break free (I.e., breakout) from landfast ice, stranding hunters on mobile ice floes.To assess this risk, a climatology of breakout events from 2000-2020 was developed, which revealed that first events in the spring now occur 46 days earlier and 6-7 more of these events now occur each year than two decades ago.Point-biserial correlations between past breakout events and meteorological variables from ECMWF's reanalysis dataset (ERA5) were calculated to explore potential associations.These yielded weak (|r| = 0.06-0.12)yet significant relationships to winds, rainfall, and snowfall.A logistic regression model to predict breakout timing outperformed climatology but had low skill.In situ observations of breakout events and environmental conditions near the floe edge are recommended to improve prediction.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".