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WA’S FIRST LARGE SCALE BENEFICIAL USE BEACH NOURISHMENT PROJECT: LESSONS LEARNED

2023· article· en· W4386969131 on OpenAlex
Demont Hansen, Jake Costin

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

VenueCoastal Engineering Proceedings · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsTransport Canada
Fundersnot available
KeywordsSeawallBeach nourishmentCoastal erosionPort (circuit theory)BreakwaterDredgingCoastal managementGeographyEnvironmental planningShoreOceanographyEngineeringGeology

Abstract

fetched live from OpenAlex

Port Beach, a popular beach in the metro area of Perth, Western Australia, is the result of 130 years of development of Fremantle Port. During many stages of development, dredged material has been disposed of at Port Beach which has resulted in a source of sand as well as undesirable material on the beach as well and in the nearshore environment. Erosion of this beach became noticeable in the 1990s and a major storm in 2003 resulted in damage to infrastructure. In 2018 Port Beach was designated the highest erosion risk beach in the Assessment of Coastal Erosion Hotspots in Western Australia by DoT and the Department of Planning, Lands, and Heritage (DPLH). In 2017, the City of Fremantle completed a Coastal Hazard Risk Management and Adaptation Plan (CHRMAP) for the Port, Leighton and Mosman Beaches in partnership with the Town of Mosman Park. Through this process, Port Beach was identified as being at extreme risk from erosion in the short term to 2030, and it was recommended that the City implement either (i) a seawall and nourishment or (ii) dune stabilisation, revegetation, and nourishment. In the longer term to 2050 onward, protection or retreat was recommended.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.003
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 head0.025
GPT teacher head0.240
Teacher spread0.215 · 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