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Record W2986626700 · doi:10.1007/s40641-019-00149-4

The Future of Midlatitude Cyclones

2019· article· en· W2986626700 on OpenAlexaff
Jennifer L. Catto, Duncan Ackerley, James F. Booth, Adrian Champion, Brian A. Colle, Stephan Pfahl, Joaquim G. Pinto, Julian Quinting, Christian Seiler

Bibliographic record

VenueCurrent Climate Change Reports · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsEnvironment and Climate Change Canada
FundersU.S. Army Corps of EngineersOak Ridge Institute for Science and EducationSight Research UKAXA Research FundNatural Environment Research CouncilU.S. ArmyMet OfficeDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsExtratropical cycloneMiddle latitudesEnvironmental scienceClimatologyCyclone (programming language)Bridging (networking)PrecipitationClimate changeMeteorologyAtmospheric sciencesGeologyGeographyComputer scienceOceanography

Abstract

fetched live from OpenAlex

Abstract Purpose of Review This review brings together recent research on the structure, characteristics, dynamics, and impacts of extratropical cyclones in the future. It draws on research using idealized models and complex climate simulations, to evaluate what is known and unknown about these future changes. Recent Findings There are interacting processes that contribute to the uncertainties in future extratropical cyclone changes, e.g., changes in the horizontal and vertical structure of the atmosphere and increasing moisture content due to rising temperatures. Summary While precipitation intensity will most likely increase, along with associated increased latent heating, it is unclear to what extent and for which particular climate conditions this will feedback to increase the intensity of the cyclones. Future research could focus on bridging the gap between idealized models and complex climate models, as well as better understanding of the regional impacts of future changes in extratropical cyclones.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.036
GPT teacher head0.283
Teacher spread0.247 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations174
Published2019
Admission routes1
Has abstractyes

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