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Record W1975983412 · doi:10.1002/hyp.7016

Assessment of annual high‐water events for the Mackenzie River basin, Canada

2008· article· en· W1975983412 on OpenAlexaffabout
Laurent P. de Rham, Terry D. Prowse, Spyros Beltaos, Martin P. Lacroix

Bibliographic record

VenueHydrological Processes · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of VictoriaImpactEnvironment and Climate Change Canada
Fundersnot available
KeywordsHydrology (agriculture)Environmental sciencePeriod (music)Drainage basinStructural basinSpring (device)DischargeMagnitude (astronomy)Return periodSTREAMSPhysical geographyGeologyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract River ice break‐up is known to have important morphological, ecological and socio‐economic effects on cold‐regions river environments. One of the most persistent effects of the spring break‐up period is the occurrence of high‐water events. A return‐period assessment of maximum annual nominal water depths occurring during the spring break‐up and open‐water season at 28 Water Survey of Canada hydrometric sites over the 1913–2002 time period in the Mackenzie River basin is presented. For the return periods assessed, 13 (14) stations are dominated by peak events occurring during the spring break‐up (open‐water) season. One location is determined to have a mixed signal. A regime classification is proposed to separate ice‐ and open‐water dominated systems. As part of the regime classification procedure, specific characteristics of return‐period patterns including alignment, and difference between the 2 and 10‐year events are used to identify regime types. A dimensionless stage‐discharge plot allows for a contrast of the relative magnitudes of flows required to generate maximum nominal water‐depth events in the different regimes. At sites where discharge during the spring break‐up is approximately one‐quarter or greater than the magnitude of the peak annual discharge, nominal water depths can be expected to exceed those occurring during the peak annual discharge event. Several physical factors (location, basin area, stream order, gradient, river orientation, and climate) are considered to explain the differing regimes and discussed relative to the major sub‐regions of the MRB. Copyright © 2008 John Wiley & Sons, Ltd and Her Majesty the Queen in right of Canada.

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 score0.056
Threshold uncertainty score0.926

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)0.0010.000

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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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

Citations33
Published2008
Admission routes2
Has abstractyes

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