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Some Characteristics of Peak Flow in the Richelieu River, Quebec

2013· article· en· W1971315300 on OpenAlexaffabout
S. Samuel Li

Bibliographic record

VenueApplied Mechanics and Materials · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsMagnitude (astronomy)Flood mythSkewnessEnvironmental scienceFlow (mathematics)Hydrology (agriculture)Rating curveDuration (music)GeographyStatisticsGeologyMathematicsPhysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

This paper presents a statistics analysis of 1938-2012 data of daily discharge and water level collected from a gauging station on the Richelieu River in Southern Quebec, Canada. Using the most recent data, this paper aims to update flood characteristics from previous decades old analyses. Such update is important to the flood-prone region. The present analysis covers peak flow magnitude, duration, timing and, more importantly, their changes. The main findings are: There are no significant changes over time in average magnitude of floods, but there are increasing fluctuations between low and high peak discharges. The distribution of annual peak discharges shows a signifcaint shift of skewness from left to right; if this condition persists, future floods are expected to have a larger magnitude than historic flood events. The timing of peak discharges has not shown any significant trend of changes. A new flow rating curve has been obtained for discharge estimates.

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)0.002
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 score0.049
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

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