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Record W3157159579 · doi:10.1080/02626667.2021.1925122

Water yield variability and response to climate change across Canada

2021· article· en· W3157159579 on OpenAlex
Zhaoqin Li, Shusen Wang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHydrological Sciences Journal · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsNatural Resources Canada
FundersNatural Resources Canada
KeywordsEvapotranspirationPrecipitationYield (engineering)Environmental scienceClimate changeStreamflowPotential evaporationWater resourcesClimatologyPhysical geographyEvaporationSurface waterWater balanceGeographyHydrology (agriculture)Drainage basinGeologyMeteorologyEcologyOceanography

Abstract

fetched live from OpenAlex

This study generated a water yield dataset for Canada for 1979–2016 by subtracting the land surface evapotranspiration (ET) and water surface evaporation (E0) from precipitation (P). The dataset was validated in Budyko space and compared with streamflow (Q) before the spatial variability and trends were analysed. Results indicate (1) uncertainties of the dataset are generally small; (2) despite the asynchronous inter-annual change, annual water yield varies in a similar temporal pattern to Q; (3) annual water yield varies dramatically across Canada, ranging from about zero on the Canadian Prairies to over 2500 mm on the West Coast; and (4) annual water yield shows no significant changes over the study period in the vast majority (82.4%) of Canada’s landmass. The most significant increasing trend appears in South Central Canada, attributed to increasing P. The most significant decreasing trend appears in Northeast Canada and the Southern Montane Cordillera, attributed to decreasing P and increasing ET.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.265
Teacher spread0.232 · 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