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Record W4410866729 · doi:10.9753/icce.v38.sediment.101

XBEACH MODELLING OF A MIXED SAND AND GRAVEL SHORELINE: EAST VANCOUVER ISLAND

2025· article· en· W4410866729 on OpenAlex
Laura Ramsden, Grant Lamont, Wil Hilsen, Phil Osborne, Neville Anne Berard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCoastal Engineering Proceedings · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsShoreGeologyGeographyOceanographyGeomorphology

Abstract

fetched live from OpenAlex

The study site is a coastal spit located in the Englishman River estuary, located at Parksville, British Columbia approximately 80 km west of Vancouver as shown in Figure 1. In this paper, we present a holistic approach to evaluating nature-based solutions and assessing coastal processes of a mixed sediment shoreline by integrating coastal process modelling using XBeach (Deltares, 2018) with geomorphic assessment This study applied a hybrid approach using both XBeach 2D which has been shown to have good quantitative skill in predicting storm response of sandy beaches and a modified 1D version, XBeach-G, which has been applied with some success to modelling uniform gravel beaches (McCall et al, 2014). The 2D (sand) and 1D (gravel) versions were applied in the surf beat mode and non- hydrostatic mode, respectively.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.572

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)0.0000.000

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 head0.168
Teacher spread0.161 · 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