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Record W2088717828 · doi:10.4296/cwrj3603889

Modes and Forcing of Hydroclimatic Variability in the Upper North Saskatchewan River Basin Since 1063

2011· article· en· W2088717828 on OpenAlexaffvenueabout
David Sauchyn, Jessica Vanstone, Cesar Perez‐Valdivia

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsStreamflowDendrochronologyStructural basinClimatologyProxy (statistics)Drainage basinForcing (mathematics)Water yearRain gaugeGeologyEnvironmental scienceHydrology (agriculture)GeographyPrecipitationMeteorologyGeomorphology

Abstract

fetched live from OpenAlex

In this paper the mean water year (October through September) flow of the North Saskatchewan River (NSR) at Edmonton, Alberta is reconstructed back to 1063 A.D. using a new network of moisture-sensitive tree-ring chronologies from limber pine and Douglas fir at seven sites in the headwater sub-basins of the North Saskatchewan River Basin (NSRB). Over the full extent of the proxy hydrometric record (10632007), we examined 1) the duration and severity of low flow, 2) the dominant frequencies of periodic variability and 3) the correlation between these significant periodicities in proxy streamflow and climate indices, specifically sea surface temperature oscillations, which are known drivers of regional hydroclimatic variability. This new record of the paleohydrology of the NSRB is compared to previous tree-ring reconstructions of the annul flow of the North and South Saskatchewan Rivers. Extending the reference hydrology for the basin from decades to centuries changes perceptions of the reliability of the water supply and understanding of the hydroclimatic variability. The gauge record not does represent the full extent of interannual to multidecadal variability in the tree-ring data; there are periods of low flow in the pre-instrumental record that are longer and more severe than those recorded by the gauge.

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)0.002
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 score0.372
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.184
Teacher spread0.165 · 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

Citations34
Published2011
Admission routes3
Has abstractyes

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