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Record W2095392363 · doi:10.1175/2008jcli2335.1

Sea Ice in the Canadian Arctic Archipelago: Modeling the Past (1950–2004) and the Future (2041–60)

2008· article· en· W2095392363 on OpenAlexaffabout
Tessa Sou, Gregory M. Flato

Bibliographic record

VenueJournal of Climate · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsPacific Institute for Climate SolutionsUniversity of Victoria
Fundersnot available
KeywordsSea iceArchipelagoArctic ice packClimatologyArctic sea ice declineEnvironmental scienceArcticCryosphereIce-albedo feedbackArctic geoengineeringAntarctic sea iceClimate modelGlobal warmingDrift iceOceanographyClimate changeGeology

Abstract

fetched live from OpenAlex

Abstract Considering the recent losses observed in Arctic sea ice and the anticipated future warming due to anthropogenic greenhouse gas emissions, sea ice retreat in the Canadian Arctic Archipelago (CAA) is expected and indeed is already being observed. As most global climate models do not resolve the CAA region, a fine-resolution ice–ocean regional model is developed and used to make a projection of future changes in the CAA sea ice. Results from a historical run (1950–2004) are used to evaluate the model. The model does well in representing observed sea ice spatial and seasonal variability, but tends to underestimate summertime ice cover. The model results for the future (2041–60) show little change in wintertime ice concentrations from the past, but summertime ice concentrations decrease by 45%. The ice thickness is projected to decrease by 17% in the winter and by 36% in summer. Based on this study, a completely ice-free CAA is unlikely by the year 2050, but the simulated ice retreat suggests that the region could support some commercial shipping.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.346
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.206
Teacher spread0.194 · 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.

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

Citations68
Published2008
Admission routes2
Has abstractyes

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