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Record W2064482501 · doi:10.1007/s10584-012-0583-5

Canadian International Polar Year (2007–2008): an introduction

2012· article· en· W2064482501 on OpenAlexaffabout
Tara Kulkarni, Joyah A. Watkins, S. Nickels, D S Lemmen

Bibliographic record

VenueClimatic Change · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsImpactInuit Tapiriit KanatamiNatural Resources CanadaFisheries and Oceans CanadaAboriginal Affairs Northern Dev Canada
Fundersnot available
KeywordsArcticCryosphereClimate changeWildlifeEnvironmental resource managementInternational communityCircumpolar starThe arcticSea iceGeographyEnvironmental sciencePhysical geographyPolitical scienceOceanographyMeteorologyEcologyGeology

Abstract

fetched live from OpenAlex

Abstract Canadian contributions to International Polar Year (IPY) 2007–2008 were designed to improve the understanding of climate change impacts and adaptation and to gain insight into issues surrounding community health and well-being in Canada’s arctic. Fifty-two research projects, involving scientists, northern partners and communities, focused on the arctic atmosphere and climate, cryosphere, oceans, sea ice, marine ecosystems, terrestrial ecosystems, wildlife as well as human health and community well-being. Key research findings on these topics are presented in this special issue of Climatic Change. This introductory paper presents an overview of the international and Canadian IPY programs and a summary of Canadian IPY results, including progress made in data management and capacity building. The legacy of IPY in Canada includes expanded international scientific cooperation, meaningful partnerships with northern communities, and more northern residents with research training.

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)0.001
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 score0.633
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.003

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 head0.090
GPT teacher head0.389
Teacher spread0.299 · 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

Citations12
Published2012
Admission routes2
Has abstractyes

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