Ocean Modification and Seasonality in a Northern Ellesmere Island Glacial Fjord Prior to Ice Shelf Breakup: Milne Fiord
Bibliographic record
Abstract
Abstract Understanding the impact of the break‐up of northern Ellesmere Island ice shelves on fjord dynamics is limited by a lack of ocean observations prior to ice loss. Based on profiling and mooring data collected between 2011 and 2019, we describe the oceanography of Milne Fiord prior to the 2020 breakup of the Milne Ice Shelf, including, sources of ambient water, under‐ice hydrography, glacial modification, and seasonality. Ambient waters originate in the Canada Basin but are modified by interaction with the 100 m thick ice shelf at the fjord entrance, and extensive glacier tongue at the head. Properties within the 436 m deep fjord are depth‐dependent, with freshwater surface runoff and subglacial discharge accumulating in the upper 50 m of the fjord each summer behind the ice shelf. Freshwater export is restricted to a basal channel in the ice shelf, resulting in the fjord being more stratified and warmer than waters offshore year‐round. Below the ice shelf and above a 260 m deep sill unrestricted exchange allows warm Atlantic Water to penetrate to the 150 m deep glacier grounding line where submarine melting occurs. Basal meltwater spreads down‐fjord close to its depth of origin due to the strong stratification. Interannual warming of fjord deepwater is likely driven by shoaling of the Arctic Ocean thermocline and spillover at the sill, highlighting the link between fjord properties and regional oceanography. Further breakup of the ice shelf is predicted to substantially alter fjord dynamics, with consequences for ocean forcing of the Milne Glacier.
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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 | 0.000 |
| 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".