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Analyzing topographic change profiles in coastal foredune systems: Methodological recommendations

2025· article· en· W4406501756 on OpenAlexafffund
Bernard O. Bauer, Jeff Ollerhead, Irene Delgado‐Fernández, Robin Davidson‐Arnott

Bibliographic record

VenueGeomorphology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsUniversity of GuelphMount Allison UniversityUniversity of British Columbia, Okanagan Campus
FundersParks Canada
KeywordsForeduneGeologyGeomorphologyOceanographyHydrology (agriculture)Physical geographyAeolian processesGeotechnical engineeringGeography

Abstract

fetched live from OpenAlex

Estimates of total sand volume in foredunes are commonly made for purposes of predicting coastal erosion and inundation potential during major storms, which is of critical importance for resource management and engineering purposes. However, changes in dune volume through time are potentially of greater relevance to process geomorphologists because volume changes are diagnostic of the long-term evolution of beach-dune systems and can be related to drivers of change (e.g., storm climatology, sediment supply, human action). The methods by which dune volume change estimates are made vary widely in the literature because there are no established protocols that provide guidance on the horizontal distances over which volume integration should be performed. In addition, identifying a diagnostic geomorphic feature such as the dune toe as a limit on integration is fraught with subjective uncertainties. In this paper, an objective methodology for quantifying dune volume change directly (rather than absolute volume) is proposed that is simple, intuitive, and robust. The horizontal limits of integration are identified by zero-crossings in the topographic change profiles between two transect surveys taken at different times, and this avoids challenges associated with identification of the dune toe as a fixed profile feature. Instead, the proposed method focuses on locations of morphodynamic significance where there has been a transition from erosion to accretion in the time interval between surveys.

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)0.001
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 score0.083
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.072
GPT teacher head0.302
Teacher spread0.229 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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