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Record W6986979026

Riverbank characteristics and stability along the upper estuarine reaches of the Moose River, northern Ontario

2000· dissertation· en· W6986979026 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2000
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsnot available
Fundersnot available
KeywordsSlumpingEstuarySiltSpring (device)Hydrology (agriculture)SedimentSnowmeltPore water pressureSnow
DOInot available

Abstract

fetched live from OpenAlex

The riverbanks within the upper reaches of the Moose River estuary have been analysed to determine their stratigraphy, geotechnical properties and stability. Rotational slumps, translational slides, block falls and earth flows are the forms of mass movement identified within the study area. Rotational slumps are the most common failure type and are particularly concentrated along the north mainland banks characterized by a basal glaciomarine unit (Tyrrell Sea clay) overlain by a thick silt unit and capped by a thin organic soil layer. The rotational slumps commonly occur in the spring and are associated with the sensitive basal stratigraphic unit (Tyrrell Sea clay). The tidal inundation and exposure of the clay twice a day encourages instability by promoting cracking which weakens the unit. Undercutting by the river flow and the scouring by river ice during spring breakup further destabilizes the bank. Coupled with an increase in pore-water pressure during snowmelt (thereby decreasing the shear strength of the sediment), and the rapid drawdown effect following the spring freshet, particularly after an ice jam, a loss of sediment strength and change in support by the river results, and large-scale failures occur.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
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 head0.014
GPT teacher head0.181
Teacher spread0.167 · 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
Published2000
Admission routes1
Has abstractyes

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