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Record W56252995

Low angle dune response to variable flow, dune translation, and crestline dynamics in Fraser Estuary, British Columbia, Canada

2014· dissertation· en· W56252995 on OpenAlexaboutno aff
M. L. Hendershot

Bibliographic record

VenueSummit (Simon Fraser University) · 2014
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsnot available
Fundersnot available
KeywordsEstuaryGeographyOceanographyGeologyFlow (mathematics)Physical geographyGeometryMathematics
DOInot available

Abstract

fetched live from OpenAlex

Dune geometry and crestline dynamics in river environments are functions of the interaction between fluid flow and the channel bed, however, little is known about how they respond to variable flow conditions in tidal environments. This study examines the evolution of a dune field in Fraser Estuary, Canada using data collected during the largest tidal flux of the neap-spring cycle on the rising limb of the annual hydrograph. Chapter One examines changes in mean geometric properties. Height and lee slope angle respond directly to changes in flow, and are linked to suspended sediment concentration flux. Height and length also show a net increase, likely responding to larger scale changes in the annual hydrograph. Chapter Two addresses crestline dynamics in response to variable flow, examining planimetric morphology, translation rates, and changes in bifurcations. Mean translation increases toward low tide with increasing mean velocity, and decreases toward high tide. Highly bifurcated areas translate farther before low tide, while areas of lower bifurcation move farther after low tide. Bifurcation ‘deaths’ outweigh ‘births’ toward low tide, indicating a shift toward a more two-dimensional planimetric morphology, while births dominate post low tide, suggesting the bed is reorganizing toward a more three-dimensional morphology.

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 score0.021
Threshold uncertainty score0.151

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 studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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
Published2014
Admission routes1
Has abstractyes

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