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Record W2891359422 · doi:10.14430/arctic4732

Arctic Sea Routes: Potential New Pathways for Nonindigenous Species Spread + Supplementary Appendix 1 (See Article Tools)

2018· article· en· W2891359422 on OpenAlexvenueno aff
Duy Nong, Amanda M. Countryman, Travis Warziniack, Erin K. Grey

Bibliographic record

VenueARCTIC · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsGeographyChinaClimate changeArcticThe arcticOceanographyEcologyBiology

Abstract

fetched live from OpenAlex

This paper evaluates the potential effects of future commercial shipping through the Northern Sea Route and Northwest Passage on the spread of nonindigenous species (NIS) between Europe, the United States, and the Asia-Pacific region. We modeled NIS spread risk as a function of two factors: NIS introduction and NIS establishment. The change in risk of NIS introduction from one region to another is based on the expected commodity trade flow between the two regions given Arctic shipping routes. The risk of NIS establishment is based on current marine climate similarities between regions and projected 2030 terrestrial climate similarities. Results indicate that the United States, China, and Japan are at greatest risk for increased terrestrial and marine NIS spread to and from one another given their relatively high levels of trading activity and terrestrial and marine climate similarities. While increased trade between European and Asia-Pacific countries is expected in the future, only Japan has terrestrial climate similar enough to that of European countries to be considered a substantial terrestrial NIS spread risk, while China has the potential to increase the risk of marine NIS species spread in Europe.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.301
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations6
Published2018
Admission routes1
Has abstractyes

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