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Record W2777741481

The nature and structure of a hanging dam in a gravel-bed river

2015· article· en· W2777741481 on OpenAlexaboutno aff
Jenna Vergeynst, Brian Morse, Benoit Turcotte

Bibliographic record

VenueGhent University Academic Bibliography (Ghent University) · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)GeologyDowntownFlood mythDeposition (geology)Flooding (psychology)OutflowGeomorphologyBreakupGeotechnical engineeringSedimentGeographyOceanographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The town of St. Raymond (QC, Canada) is subject to frequent ice-induced flooding of the St. Anne River. In addition to breakup ice jams, a major cause of winter flooding is associated with massive frazil deposition in the form of a hanging dam in the downtown reach of the river. Recent studies have identified a number of potential solutions to attenuate the flood risk. An important aspect of these solutions is associated with the reduction of frazil deposition, which amount had not been estimated before. The purpose of this study was to answer this need by quantifying the hanging dam’s dimensions (volume and mass) and structure. The 2014-2015 frazil dam’s length was 9.5 km, its volume was 620 000 m3 and its mass was 440 000 tons. Most of the hanging dam mass (74%) originated from the upstream part of the St. Anne River, where frazil transport in the water column was measured by manual sampling. In turn, most of the frazil was deposited in the downtown reach because of low velocities caused by the presence of the Chute-Panet dam located 3 km downstream of the town. The hanging dam core was also surveyed at multiple cross-sections. It presented frazil layers and accumulation zones of different densities. The hanging dam structure presented a greater complexity in town and was simpler near its head and its toe.

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 score0.099
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.011
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.187
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 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

Citations2
Published2015
Admission routes1
Has abstractyes

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