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Engineering Evaluation of Freshwater Lake Coastal Sand Dunes: A Study of Sandbanks Provincial Park, Kingston, Canada

2025· article· en· W4408184262 on OpenAlexaboutno aff
Indra Prakash, Sarita Singh, Binh Thai Pham

Bibliographic record

VenueJournal of Science and Transport Technology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
Fundersnot available
KeywordsGeographySand dune stabilizationArchaeologyHydrology (agriculture)GeologyGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

This study provides a comprehensive engineering evaluation of the freshwater coastal sand dunes at Sandbanks Provincial Park, located on the southern edge of Prince Edward County, Kingston, Ontario, Canada. Sandbanks is renowned for its extensive and dynamic sand dune system, which plays a crucial role in coastal management by absorbing wave energy, mitigating storm surges, and preventing sand deposition on infrastructure. Shaped by historical glacial activities, wind, and wave action, these dunes are critical for stabilizing the beach environment, controlling wind erosion, and supporting diverse plant and animal communities. This research uniquely combines historical data with recent field studies to offer new insights into the engineering properties, geomorphological processes, and ecological dynamics that govern the formation, stability, and resilience of the dunes. The study addresses contemporary challenges such as climate change, human impact, and erosion, and proposes actionable conservation strategies that balance ecological preservation with practical land management. While focused on a specific section of Ontario’s coastal dunes, the findings contribute to a deeper understanding of coastal dune systems more broadly, offering valuable guidance for their long-term sustainability and management across similar environments.

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 score0.700
Threshold uncertainty score0.979

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)0.0000.000

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 head0.006
GPT teacher head0.207
Teacher spread0.202 · 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
Published2025
Admission routes1
Has abstractyes

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