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Record W1705283903 · doi:10.1029/2011wr010930

Groundwater levels and teleconnection patterns in the Canadian Prairies

2012· article· en· W1705283903 on OpenAlexaffabout
Cesar Perez‐Valdivia, D. Sauchyn, Jessica Vanstone

Bibliographic record

VenueWater Resources Research · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsTeleconnectionPacific decadal oscillationMultivariate ENSO indexEnvironmental scienceGroundwaterClimatologyGroundwater rechargeEl Niño Southern OscillationPrecipitationClimate changeHydrology (agriculture)La NiñaAquiferGeologyGeographyOceanographyMeteorology

Abstract

fetched live from OpenAlex

Thirty one hydrological time series of shallow groundwater levels, precipitation, and moisture‐sensitive tree ring chronologies were analyzed and related to two climate indices: Niño 3.4 and PDO. Spearman rank correlation and spectral analyses (multitaper method, continuous wavelet transform, and wavelet coherence) were used to document the influence of El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) on shallow (depth < 20 m) groundwater level records from the Canadian Prairies. Modes of variability in the 2–7, 7–10, and 18–22 year bands were detected and reconstructed. Correlations and wavelet coherence between these oscillation modes and the climate indices suggest that variability in the 2–7 and 7–10 year bands is highly influenced by ENSO. The oscillation modes in the 18–22 year band reflect a negative correlation with the PDO index. When either of these teleconnections (ENSO/PDO) is in their respective positive phases, groundwater levels reflect the effect of associated warmer and drier winters experienced over much of interior Canada and the US, affecting important resource inputs to the hydrological cycle and groundwater recharge.

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 score0.036
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
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.090
GPT teacher head0.309
Teacher spread0.219 · 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

Citations85
Published2012
Admission routes2
Has abstractyes

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