Variability in the Distribution of Fast Ice and the Sub‐ice Platelet Layer Near McMurdo Ice Shelf
Bibliographic record
Abstract
Abstract Variability in the volume of supercooled Ice Shelf Water outflow in McMurdo Sound is reflected in the thickness and distribution of fast ice and the sub‐ice platelet layer beneath. Ground‐based electromagnetic induction and drill hole surveys of the distribution and thickness of ice shelf‐influenced fast ice and the sub‐ice platelet layer in McMurdo Sound were carried out in late spring of 2011, 2013, 2016, and 2017. In 2011 and 2017, thicker sub‐ice platelet layers of up to 7.5 and 6 m were observed, respectively. Fast ice formation throughout the winters of 2011 and 2017 was influenced by a higher occurrence of strong southerly wind events and resultant activity of the Ross Sea Polynya. In contrast, lower wind conditions in 2016 led to largely undisturbed sea ice growth and anomalously extensive fast ice coverage. A thinner sub‐ice platelet layer of up to 4 m was observed in 2016. In 2011 and 2017, substantial and variable sub‐ice platelet layers were detected in a region of exchange of water masses between the Ross Sea and the McMurdo‐Ross ice shelf cavity, which were not observed in 2013 and 2016. We hypothesize that a higher frequency of strong southerly wind events, resultant polynya activity, and High Salinity Shelf Water production over winter accelerates circulation and increases melting in the proximal shallow McMurdo Ice Shelf and the deeper Ross Ice Shelf regions of the conjoined cavity. The outflow of supercooled Ice Shelf Water and sub‐ice platelet layer formation in McMurdo Sound are consequently promoted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".