Sea ice draft observations in <scp>N</scp>ares <scp>S</scp>trait from 2003 to 2012
Bibliographic record
Abstract
Abstract Time series observation of sea ice draft and velocity from Nares Strait between 2003 and 2012 provides new insights on the statistical properties of sea ice leaving the Arctic for the Atlantic Oceans. Median ice draft is 0.8 m, but it varies annually from 1.5 m in 2007–2008 to 0.5 m in 2008–2009. Probability density distributions of sea ice draft depend on location across the channel with thicker ice near Canada and thinner ice near Greenland. Nevertheless, sea ice motion stops seasonally due to arching land‐fast ice that spans the 30–40 km wide channel for up to 190 days per year such as during the 2011–2012 winter. In contrast, the 2006–2010 period exhibits a single ice arch lasting 47 days in April/May 2008. Hence sea ice statistics are weighted by space not by time, using sea ice velocities estimated from colocated velocity observations. Multiyear sea ice with drafts exceeding 5 m constitute between 9% (2003–2004) and 16% (2007–2008) of the observed sea ice. The probability g(D) of this thick, ridged, multiyear ice decays exponentially with draft D at an e‐folding scale D0 of 3.0 ± 0.2 m. The trend of D0 with time is statistically indistinguishable from zero. This observation suggests a steady export of multiyear sea ice at decadal time scales. We speculate that our observations document the draining of the last reservoir of thick ice from the Arctic Ocean found to the north of Ellesmere Island and Greenland.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".