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Record W2914517338 · doi:10.3390/jmse7020034

Hard-Rock Coastal Modelling: Past Practice and Future Prospects in a Changing World

2019· article· en· W2914517338 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Marine Science and Engineering · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBeach morphodynamicsCliffIntertidal zoneErosionCoastal erosionGeologyShoreSedimentWeatheringOceanographySedimentary budgetSediment transportEarth scienceGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

This paper reviews the history of conceptual and numerical modelling of hard rock coasts (mean annual cliff erosion typically < 1 mm up to 1 cm) and its use in studying coastal evolution in the past and predicting the impact of the changing climate, and especially rising sea level, in the future. Most of the models developed during the last century were concerned with the development and morphology of shore-normal coastal profiles, lacking any sediment cover, in non-tidal environments. Some newer models now consider the plan shape of rock coasts, and models often incorporate elements, such as the tidally controlled expenditure of wave energy within the intertidal zone, beach morphodynamics, weathering, changes in relative sea level, and the role of wave refraction and sediment accumulation. Despite these advances, the lack of field data, combined with the inherent complexity of rock coasts and uncertainty over their age, continue to inhibit attempts to develop more reliable models and to verify their results.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.179
Teacher spread0.173 · 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