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Record W3109630103 · doi:10.1016/j.ejrh.2020.100754

18O and 2H in streamflow across Canada

2020· article· en· W3109630103 on OpenAlexafffundabout
J. J. Gibson, Tegan Holmes, Tricia Stadnyk, S. J. Birks, P. Eby, Alain Pietroniro

Bibliographic record

VenueJournal of Hydrology Regional Studies · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of ManitobaUniversity of CalgaryUniversity of Victoria
FundersInnotech AlbertaEnvironment and Climate Change Canada
KeywordsStreamflowδ18OTributaryPrecipitationSnowHydrology (agriculture)Environmental sciencePermafrostArcticDrainage basinMeteoric waterPhysical geographyStable isotope ratioClimatologyGeologyGroundwaterGeographyOceanographyMeteorologyGeomorphology

Abstract

fetched live from OpenAlex

Water samples for isotopic analysis were collected during 2013–2019 at 331 gauging stations across Canada in representative watersheds ranging from the Atlantic to the Pacific to the Arctic Oceans. Drainage area coverage of the network included 56 % of Canada’s landmass (9,984,670 km2) and was representative of 91 % of Canada’s annual water yield. Baseline data, including 4603 18O and 2H analyses, are described to assess potential for process studies and predictive model calibration. While similar patterns are noted between isotopes in streamflow and precipitation across Canada, systematic evaporative enrichment in streamflow occurs in lake- and wetland-rich areas, and systematic depletion occurs in some mountainous and/or cold-regions watersheds. The latter are attributed to uncertainty in precipitation isotope records, glacial melt and/or permafrost thaw. In δ18O-δ2H space, streamflow characteristically plotted on or below the Canadian Meteoric Water Line (CMWL) (δ2H = 8∙δ18O+8.5) along imbricated Regional River Lines (RRL) displaying a range of regression slopes (4.34–9.31) and intercepts (-54 to +24), reflecting regional variations in isotopic composition of input sources, evaporative enrichment, and tributary mixing. We define the Canadian Rivers Line (CRL) based on the linear regression of flow-weighted mean values of station data (δ2H = 7.89∙δ18O+0.45, r2 = 0.962; n = 161).

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

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

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 head0.034
GPT teacher head0.243
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 teacher head, 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

Citations36
Published2020
Admission routes3
Has abstractyes

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