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Record W2969842818 · doi:10.5194/hess-23-3437-2019

Summary and synthesis of Changing Cold Regions Network (CCRN) research in the interior of western Canada – Part 1: Projected climate and meteorology

2019· article· en· W2969842818 on OpenAlexafffundabout
Ronald E. Stewart, Kit K. Szeto, Barrie Bonsal, John Hanesiak, Bohdan Kochtubajda, Yanping Li, Julie M. Thériault, C. M. DeBeer, Benita Y. Tam, Zhenhua Li, Zhuo Liu, Jennifer Bruneau, Patrick Duplessis, Sébastien Marinier, Dominic Matte

Bibliographic record

VenueHydrology and earth system sciences · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsDalhousie UniversityGlobal Institute for Water SecurityCenter for Diagnosis and Research on Alzheimer's DiseaseUniversity of SaskatchewanEnvironment and Climate Change CanadaUniversité du Québec à MontréalUniversity of Manitoba
FundersGlobal Water FuturesUniversité du Québec à MontréalNatural Sciences and Engineering Research Council of CanadaH2020 European Research CouncilCanada First Research Excellence FundEnvironment and Climate Change CanadaCompute Canada
KeywordsEnvironmental scienceClimatologyWinter stormClimate changePrecipitationForcing (mathematics)Freezing rainAtmospheric sciencesStormMeteorologyGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

The interior of western Canada, up to and including the Arctic, has experienced rapid change in its climate, hydrology, cryosphere, and ecosystems, and this is expected to continue. Although there is general consensus that warming will occur in the future, many critical issues remain. In this first of two articles, attention is placed on atmospheric-related issues that range from large scales down to individual precipitation events. Each of these is considered in terms of expected change organized by season and utilizing mainly “business-as-usual” climate scenario information. Large-scale atmospheric circulations affecting this region are projected to shift differently in each season, with conditions that are conducive to the development of hydroclimate extremes in the domain becoming substantially more intense and frequent after the mid-century. When coupled with warming temperatures, changes in the large-scale atmospheric drivers lead to enhancements of numerous water-related and temperature-related extremes. These include winter snowstorms, freezing rain, drought, forest fires, as well as atmospheric forcing of spring floods, although not necessarily summer convection. Collective insights of these atmospheric findings are summarized in a consistent, connected physical framework.

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)0.003
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.031
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.057
GPT teacher head0.265
Teacher spread0.208 · 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
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

Citations20
Published2019
Admission routes3
Has abstractyes

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