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Record W4408340948 · doi:10.1038/s43247-025-02180-w

Author Correction: Arctic food and energy security at the crossroads

2025· article· en· W4408340948 on OpenAlexaff
Adrian Unc, Majdi Abou Najm, Paul Eric Aspholm, Tirupati Bolisetti, Colleen Charles, Ranjan Datta, Trine Eggen, Belinda Flem, Getu Hailu, Eldbjørg S. Heimstad, Margot Hurlbert, Meriam G. Karlsson, Marius Korsnes, Arthur Nash, David Parsons, Radha Sivarajan Sajeevan, Narasinha Shurpali, Govert Valkenburg, Danielle Wilde, Bing Wu, Sandra F. Yanni, Debasmita Misra

Bibliographic record

VenueCommunications Earth & Environment · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsAgriculture and Agri-Food CanadaMount Royal UniversityUniversity of ReginaMcGill UniversityFirst Nations University of CanadaUniversity of WindsorMemorial University of Newfoundland
Fundersnot available
KeywordsArcticFood securityThe arcticEnvironmental scienceEnergy (signal processing)GeographyOceanographyGeologyMathematicsStatisticsArchaeologyAgriculture

Abstract

fetched live from OpenAlex

Correction to: Communications Earth & Environment https://doi.org/10.1038/s43247-025-02122-6 , published online 18 February 2025

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)0.003
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.062
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0070.013
Insufficient payload (model declined to judge)0.0770.043

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 head0.027
GPT teacher head0.303
Teacher spread0.276 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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