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Record W2000785775 · doi:10.1029/2001gl013827

A coupled atmospheric‐hydrological modeling study of the 1996 Ha! Ha! River basin flash flood in Québec, Canada

2002· article· en· W2000785775 on OpenAlexaffabout
Charles A. Lin, Lei Wen, Michel Béland, Diane Chaumont

Bibliographic record

VenueGeophysical Research Letters · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsCompute CanadaMcGill University
Fundersnot available
KeywordsHydrographFlash floodHydrology (agriculture)Routing (electronic design automation)Flood mythDrainage basinPrecipitationEnvironmental scienceStructural basinFlood forecastingGeologyHydrological modellingRain gaugeMeteorologyClimatologyGeomorphologyGeographyCartography

Abstract

fetched live from OpenAlex

We use a high‐resolution regional atmospheric model coupled to a hydrological model, and an off‐line routing module to simulate a hydrograph during the 1996 July flash flood that occurred in the Saguenay region of eastern Québec. The hydrograph is at the outlet of the Ha! Ha! Lake in the Ha! Ha! River basin. The former has a drainage area of 250 km2 and is covered by 6 model grid squares; the precipitation at these grid squares compare well with observations at the nearest available rain gauge located 20 km south of the basin. The hydrological model is a modified version of a land surface scheme which consists of three soil layers, and the routing module is based on the geomorphological unit hydrograph. The simulated hydrograph is compared with another reconstructed hydrograph in the published literature.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.244
Teacher spread0.216 · 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 designSimulation or modeling
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

Citations28
Published2002
Admission routes2
Has abstractyes

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