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Record W2099600045 · doi:10.14430/arctic98

The Changing Climate of the Arctic

2009· article· en· W2099600045 on OpenAlexaffvenueabout
David G. Barber, Jennifer V. Lukovich, John Keogak, Steven Baryluk, Louis Fortier, Greg H. R. Henry

Bibliographic record

VenueARCTIC · 2009
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British ColumbiaUniversité LavalUniversity of Manitoba
Fundersnot available
KeywordsClimate changeArcticThermohaline circulationGlobal warmingClimatologySea iceEnvironmental scienceOceanographyArctic ice packEffects of global warmingGlobal changeGeographyGeology

Abstract

fetched live from OpenAlex

The first and strongest signs of global-scale climate change exist in the high latitudes of the planet. Evidence is now accumulating that the Arctic is warming, and responses are being observed across physical, biological, and social systems. The impact of climate change on oceanographic, sea-ice, and atmospheric processes is demonstrated in observational studies that highlight changes in temperature and salinity, which influence global oceanic circulation, also known as thermohaline circulation, as well as a continued decline in sea-ice extent and thickness, which influences communication between oceanic and atmospheric processes. Perspectives from Inuvialuit community representatives who have witnessed the effects of climate change underline the rapidity with which such changes have occurred in the North. An analysis of potential future impacts of climate change on marine and terrestrial ecosystems underscores the need for the establishment of effective adaptation strategies in the Arctic. Initiatives that link scientific knowledge and research with traditional knowledge are recommended to aid Canada’s northern communities in developing such strategies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.975

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.357
Teacher spread0.327 · 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

Citations110
Published2009
Admission routes3
Has abstractyes

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