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Record W2914238061 · doi:10.1017/s0032247418000645

The Permafrost Young Researchers Network (PYRN) is getting older: The past, present, and future of our evolving community

2019· article· en· W2914238061 on OpenAlexaff
George Tanski, Helena Bergstedt, Alexandre Bevington, Philip P. Bonnaventure, Frédéric Bouchard, Caroline Coch, Simon Dumais, Alevtina Evgrafova, Oliver W. Frauenfeld, Jennifer Frederick, Michael Fritz, D. М. Frolov, Silvie Harder, Ingo Hartmeyer, Joanne Heslop, Elin Hogström, Margareta Johansson, Gleb Kraev, Elena Kuznetsova, Josefine Lenz, A. V. Lupachev, Florence Magnin, Jannik Martens, Alexey Maslakov, Anne Morgenstern, Alexandre Nieuwendam, Marc Oliva, Boris Radosavljevic, Justine Ramage, Andrea Schneider, Julia Stanilovskaya, Jens Strauß, Erin Trochim, Daniel J. Vecellio, Samuel Weber, Hugues Lantuit

Bibliographic record

VenuePolar Record · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsQueen's UniversityMcGill UniversityUniversity of LethbridgeUniversité LavalGovernment of British Columbia
Fundersnot available
KeywordsThrivingPermafrostOutreachCensusPromotion (chess)Public relationsPolitical scienceSociologyEcologySocial scienceLawPoliticsBiology

Abstract

fetched live from OpenAlex

Abstract A lasting legacy of the International Polar Year (IPY) 2007–2008 was the promotion of the Permafrost Young Researchers Network (PYRN), initially an IPY outreach and education activity by the International Permafrost Association (IPA). With the momentum of IPY, PYRN developed into a thriving network that still connects young permafrost scientists, engineers, and researchers from other disciplines. This research note summarises (1) PYRN’s development since 2005 and the IPY’s role, (2) the first 2015 PYRN census and survey results, and (3) PYRN’s future plans to improve international and interdisciplinary exchange between young researchers. The review concludes that PYRN is an established network within the polar research community that has continually developed since 2005. PYRN’s successful activities were largely fostered by IPY. With >200 of the 1200 registered members active and engaged, PYRN is capitalising on the availability of social media tools and rising to meet environmental challenges while maintaining its role as a successful network honouring the legacy of IPY.

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)0.015
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0070.007
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.043
GPT teacher head0.275
Teacher spread0.231 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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