WA’S FIRST LARGE SCALE BENEFICIAL USE BEACH NOURISHMENT PROJECT: LESSONS LEARNED
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".