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Record W3175471380 · doi:10.1139/facets-2020-0096

Changes in shipping navigability in the Canadian Arctic between 1972 and 2016

2021· article· en· W3175471380 on OpenAlexafffundvenueabout
Luke Copland, Jackie Dawson, Adrienne Tivy, Frances Delaney, Alison Cook

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Ottawa
FundersTransport CanadaNatural Sciences and Engineering Research Council of CanadaMarine Environmental Observation Prediction and Response NetworkArcticNetUniversity of Ottawa
KeywordsNavigabilityArcticArctic ice packSea icePhysical geographyOceanographyBayGeographyEnvironmental scienceClimatologyMeteorologyGeologyCartography

Abstract

fetched live from OpenAlex

There have been rapid recent reductions in sea ice age and extent in the Canadian Arctic, but little previous analysis of how this has impacted the navigability of Arctic shipping. In this study we analyze how navigability changed over the period 1972–2016 by converting Canadian Ice Service ice charts to shipping navigability charts for different hull strength classifications based on the Arctic Ice Regime Shipping System. Analysis focuses on the southern route of the Northwest Passage, and the Arctic Bridge route across Hudson Bay, for changes in early-season (∼25 June), mid-season (∼3 September), and late-season (∼15 October) conditions. Results reveal that there has been a marked easing in shipping navigability for all vessels over the past decade, driven by reductions in the area and age of sea ice, particularly across the southern route of the Northwest Passage. Both medium (Type B) and little (Type E) ice strengthened vessels were able to transit the full length of this route in the middle part of the shipping season in 2012–2016, but not in 1972–1976 or 1992–1996.

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)0.001
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 score0.018
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.022
GPT teacher head0.227
Teacher spread0.206 · 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

Citations26
Published2021
Admission routes4
Has abstractyes

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Same venueFACETSSame topicArctic and Antarctic ice dynamicsFrench-language works237,207