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Record W4388648401 · doi:10.5194/esd-14-1165-2023

ESD Ideas: Arctic amplification's contribution to breaches of the Paris Agreement

2023· article· en· W4388648401 on OpenAlexaff
Alistair Duffey, Robbie Mallett, Peter Irvine, Michel Tsamados, Julienne Strœve

Bibliographic record

VenueEarth System Dynamics · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Manitoba
FundersNatural Environment Research CouncilSight Research UKEuropean Space Agency
KeywordsCognitive reframingArcticThe arcticGlobal warmingClimate changeEnvironmental scienceClimatologyOceanographyPsychologyGeologySocial psychology

Abstract

fetched live from OpenAlex

Abstract. The Arctic is warming at almost 4 times the global average rate. Here we reframe this amplified Arctic warming in terms of global climate ambition to show that without Arctic amplification, the world would breach the Paris Agreement's 1.5 and 2 ∘C limits 5 and 8 years later, respectively. We also find the Arctic to be a disproportionate contributor to uncertainty in the timing of breaches. The outsized influence of Arctic warming on global climate targets highlights the need for better modelling and monitoring of Arctic change.

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)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.005
Scholarly communication0.0070.004
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.002

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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 designSimulation or modeling
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

Citations11
Published2023
Admission routes1
Has abstractyes

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