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Record W2071630498 · doi:10.1029/2005gl022845

Decreasing river discharge in northern Canada

2005· article· en· W2071630498 on OpenAlexaboutno aff
Stephen J. Déry, Eric F. Wood

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersArmy Research Office
KeywordsDischargeArcticArchipelagoEnvironmental scienceNorth Atlantic oscillationPacific decadal oscillationSurface runoffPrecipitationLatitudeClimatologyNorthern HemisphereArctic oscillationOceanographySink (geography)The arcticHydrology (agriculture)Drainage basinGeologyEl Niño Southern OscillationGeographyMeteorologyEcology

Abstract

fetched live from OpenAlex

Freshwater discharge to high‐latitude oceans in 64 Canadian rivers is investigated. The mean annual discharge rate attains 1252 km3 yr−1 for an area of 5.6 × 106 km2, equating to a sink of 225 mm yr−1 in the surface water budget of northern Canada (excluding the Arctic Archipelago where insufficient data exist). Application of the Mann‐Kendall test to the data reveals a 10% decrease (−125 km3 yr−1 or −22 mm yr−1) in the total annual river discharge to the Arctic and North Atlantic Oceans from 1964 to 2003. This trend in river runoff is consistent with a 21 mm yr−1 decline in observed precipitation over northern Canada between 1964 and 2000. We find evidence of statistically‐significant links between the Arctic Oscillation, El Niño/Southern Oscillation, and the Pacific Decadal Oscillation to the total annual freshwater discharge in northern Canada's rivers at interannual‐to‐decadal timescales.

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 score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.046
GPT teacher head0.285
Teacher spread0.239 · 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

Citations278
Published2005
Admission routes1
Has abstractyes

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