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Record W7043065806

Sedimentation of coastal foredunes at Greenwich Dunes, Prince Edward Island

2004· dissertation· en· W7043065806 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2004
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
Fundersnot available
KeywordsForeduneGreenwichDeposition (geology)Sediment transportAeolian processesHydrology (agriculture)SedimentVegetation (pathology)
DOInot available

Abstract

fetched live from OpenAlex

This thesis is an investigation of the nature of sedimentation of vegetated foredunes, at Greenwich Dunes, Prince Edward Island, Canada. Seasonal measurements of deposition and erosion and vegetation growth on the foredune were made at monitoring profiles of varying morphology and vegetation characteristics. Short term measurements of winds and saltation intensity were made on the beach and up the stoss slope of the foredune. Wind speed and direction measurements were made with arrays of cup anemometers and a 2-D sonic anemometer. Sediment transport intensity was measured using Sabatech omnidirectional saltation probes, which count the impact of saltating sand grains on a piezoelectric crystal. Measurements of winds and saltation were made on the stoss slope of a vegetated foredune with varying vegetation cover. Long term monitoring of foredune development show distinct spatial and seasonal patterns of sedimentation related to wind climate, vegetation and morphology. The majority of sediment is deposited in the autumn season, from September to December, when strong, highly oblique winds out of the west and northwest are common. The greatest accumulations generally occur within 5 m either side of the foredune crest. The summer season has much lower accumulations, and these occur mainly at the toe and lower dune locations. The winter-spring period displays significant amounts of sediment deposition and erosion, with a tendency towards deposition in lee of the crest. (Abstract shortened by UMI.)

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 score0.317
Threshold uncertainty score0.996

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)0.0010.000

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 head0.007
GPT teacher head0.199
Teacher spread0.191 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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