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Record W1947562441 · doi:10.1029/2008wr007639

New reconstructions of streamflow variability in the South Saskatchewan River Basin from a network of tree ring chronologies, Alberta, Canada

2009· article· en· W1947562441 on OpenAlexaffabout
Jodi Axelson, David Sauchyn, Jonathan Barichivich

Bibliographic record

VenueWater Resources Research · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of ReginaNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsStreamflowWater yearProxy (statistics)Drainage basinDendrochronologyClimatologyStructural basinHistorical recordEnvironmental scienceHydrology (agriculture)Water resourcesPhysical geographyGeographyGeologyArchaeologyCartographyGeomorphology

Abstract

fetched live from OpenAlex

In western Canada growing demand for water resources has increased vulnerability to hydrological drought. The near full allocation of water supplies in the Oldman and Bow River subbasins of the South Saskatchewan River Basin has resulted in a moratorium on new surface water licenses. In this region, short instrumental records limit the detection of long‐term hydrological variability. To extend the historical record, we collected 14 new moisture‐sensitive tree ring chronologies and reconstructed the average October through September flow of the Oldman (1618–2004) and South Saskatchewan (SSR) (1400–2004) rivers. Our SSR proxy record updates a previously published reconstruction. While the 20th century is representative of drought frequency over the long term, droughts are of greater severity and duration in the preinstrumental proxy record. A spectral analysis of the reconstructed flows revealed quasiperiodic cycles at interannual to multidecadal scales.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.244
Teacher spread0.218 · 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 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

Citations75
Published2009
Admission routes2
Has abstractyes

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