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Record W1991448376 · doi:10.1029/2009gl037681

Sea ice conditions and melt season duration variability within the Canadian Arctic Archipelago: 1979–2008

2009· article· en· W1991448376 on OpenAlexaffabout
Stephen Howell, Claude Duguay, T. Markus

Bibliographic record

VenueGeophysical Research Letters · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsArcticArchipelagoSea iceArctic ice packClimatologyOceanographyArctic sea ice declineEnvironmental scienceGeologyAntarctic sea ice

Abstract

fetched live from OpenAlex

Sea ice conditions and melt season duration within the Canadian Arctic Archipelago (CAA) were investigated from 1979–2008. The CAA is exhibiting statistically significant decreases in average September total sea ice area at −8.7% decade−1. The melt season duration within the CAA is increasing significantly at 7 days decade−1. 2008 represented the longest melt season duration within the CAA over the satellite record at 129 days. Average September multi‐year ice (MYI) area is decreasing at −6.4% decade−1 but has yet to reach statistical significance as a result of increasing MYI dynamic import from the Arctic Ocean. Results also find that the Western Parry Channel (WPC) region of the Northwest Passage (NWP) will continue to be susceptible to MYI as the transition to a summer‐time sea ice free Arctic continues. The processes responsible for the temporary clearing of the WPC region of the NWP in 2007 were also identified.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations144
Published2009
Admission routes2
Has abstractyes

Explore more

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