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Record W1597237700 · doi:10.20381/ruor-13710

Changes in Multiyear Landfast Sea Ice in the Northern Canadian Arctic Archipelago

2010· dissertation· en· W1597237700 on OpenAlexaboutno aff
Sierra Pope

Bibliographic record

VenueuO Research (University of Ottawa) · 2010
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsArchipelagoOceanographyArcticSea iceGeographyThe arcticArctic ice packClimatologyPhysical geographyGeology

Abstract

fetched live from OpenAlex

For most of the 20th century, multiyear landfast sea ice (MLSI) existed in semi-permanent plugs across Nansen Sound and Sverdrup Channel and formed an incipient ice shelf in Yelverton Bay, Ellesmere Island in the northern CAA. Both plugs broke in 1962 and 1998, and several breakups within the last decade indicate that the plugs are becoming temporary seasonal features. The history of the plugs is reviewed using Canadian Ice Service ice charts, satellite imagery and a literature review. The weather systems associated with plug breakup events are related to a sequence of synoptic patterns, with most breakups occurring when low pressure centers over the Asian side of the Arctic Ocean and a warm pressure ridge develops over the QEI, creating warm temperatures, clear skies, and frequent wind reversals. The 2005 simultaneous breakup of the plugs was accompanied by the removal of 690 km2 of 55-60 year old MLSI from Yelverton Bay. Ground Penetrating Radar (GPR) and ice cores taken in June 2009 provide the first detailed assessment of the remaining MLSI in Yelverton Inlet, which in turn provides ground-truthing of satellite scenes and air photos used to chart historical changes in the MLSI. The last of the Yelverton Bay MLSI was removed in August 2010. The removal of these MLSI features in recent years aligns with the larger trend of reductions in age and thickness of sea ice in the Canadian Arctic Archipelago.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.243
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2010
Admission routes1
Has abstractyes

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