MétaCan
Menu
Back to cohort
Record W4400531426 · doi:10.1038/s43247-024-01477-6

Sea ice choke points reduce the length of the shipping season in the Northwest Passage

2024· article· en· W4400531426 on OpenAlexaffabout
Alison Cook, Jackie Dawson, Stephen Howell, Jean Holloway, Mike Brady

Bibliographic record

VenueCommunications Earth & Environment · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Ottawa
Fundersnot available
KeywordsChokeArcticEnvironmental scienceSea icePhysical geographyArctic ice packThe arcticGrowing seasonLatitudeGeographyClimatologyOceanographyMeteorologyGeologyEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Abstract Arctic sea ice has shifted from a perennial (older, thicker ice) to a seasonal (younger, thinner) ice regime, leading to the increasingly common belief that shipping through Canada’s Northwest Passage is becoming more viable. Here, we use the Risk Index Outcome values derived from the Polar Operational Limit Assessment Risk Indexing System and analyze recent changes to shipping season lengths along individual sections of the Northwest Passage routes from 2007 to 2021. Results show that multi-year ice flushed southward from high-latitude regions maintains the so-called choke points along certain route sections, reducing overall shipping season length. There is considerable spatiotemporal variability in shipping season lengths along the southern and northern routes. Specifically, parts of the northern route exhibit a decrease of up to 14 weeks over the 15 years. The variability of shipping season and, in particular, the shortening of the season will impact not only international shipping but also resupply and the cost of food in many Arctic communities, which require a prompt policy response.

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)0.002
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 score0.922
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.314
Teacher spread0.265 · 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

Citations25
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCommunications Earth & EnvironmentSame topicArctic and Russian Policy StudiesFrench-language works237,207