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Record W7099381278

and Assiniboine River Water Levels

2013· article· en· W7099381278 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)Flood mythDrainage basinChannel (broadcasting)StormFloodplainAlluvial fanWater levelAlluvium
DOInot available

Abstract

fetched live from OpenAlex

peaked in late July, 2011 although a significant windstorm on May 31 caused even higher wind affected water levels on the south basin of the lake. It was during this storm event that many homes and cottages in the south basin of the lake were destroyed or damaged. The topographic features of the lower Assiniboine River are noteworthy because they have consequences during large flood events. Historic floods have resulted in water overflowing the low banks of the river and spreading out across the prairie, often inundating large areas of land. After the last ice age, from Portage la Prairie downstream, the Assiniboine River built an alluvial fan, a collection of channels built by the river depositing sediment as it descends to the lower level of the glacial Lake Agassiz plain. The river in this stretch is unstable since portions of the riverbed are perched above the elevation of the surrounding land. As a result, the river has changed its course numerous times over the past millennia, abandoning its channel in favour of lower, more stable routes, which are later abandoned. The former channels, called paleochannels, radiate in an arc of 180 degrees with some flowing north to end in Lake Manitoba and others continuing east to join the Red River. These channels play a significant role during flood events because, when the river overflows its banks, the paleochannels convey a portion of the overflows downstream to neighbouring watersheds.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

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)0.0100.001

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 head0.008
GPT teacher head0.183
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

Study designOther design
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 routes1
Has abstractyes

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