Landfast ice properties over the Beaufort Sea region in 2000–2019 from MODIS and Canadian Ice Service data
Bibliographic record
Abstract
Two decades (2000–2019) of the landfast ice properties in the Beaufort Sea region in the Canadian Arctic were analyzed at 250 m spatial resolution from two sources: (1) monthly maps derived at the Canada Centre for Remote Sensing from the Moderate Resolution Imaging Spectroradiometer clear-sky satellite image composites; and (2) Canadian Ice Service charts. Detailed comparisons have been conducted for the landfast ice spatial extent, the water depth at, and the distance to the outer seaward edge from the coast in four sub-regions: (1) Alaska coast; (2) Barter Island to Herschel Island; (3) Mackenzie Bay; and (4) Richards Island to Cape Bathurst. The results from both sources demonstrate good agreement. The average spatial extent for the entire region over the April–June period is 48.5 (±5.0) × 10 3 km 2 from Canadian Ice Service data versus 45.1 (±6.1) × 10 3 km 2 from satellite data used in this study (7.0% difference). The correlation coefficient for April–June is 0.73 (p = 2.91 × 10 −4 ). The long-term linear trends of the April–June spatial extent since 2000 demonstrated statistically significant decline: −4.45 (±1.69) × 10 3 km 2 /decade and −4.73 (±2.17) × 10 3 km 2 /decade from Canadian Ice Service and satellite data, respectively. The landfast ice in the Beaufort Sea region showed the general tendency for an earlier break-up, later onset, and longer ice-free period. The break-up date has decreased by 7.6 days/decade in the Mackenzie Bay region. The western part of the study area did not demonstrate statistically significant changes since 2000.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".