Bibliographic record
Abstract
Beach, and particularly profile nourishment is not a universally accepted solution for coastal protection. ha cost has been criticized; its temporary remedial nature emphasized. However, no better, less expensive solution has been proposed Let nature take its course is indeed the simplest approach but one that in many instances does not face up to economic realities. Belgium's coastline is short and its occupation is intensive. Politically and economically it cannot be left to evolve without intervention. Traditionally groins have been constructed to hold off the assault of the sea and retain sand for the beaches This approach has proven to be unsatisfactory, even damaging A major beach nourishment program was undertaken at the eastern end; at that time, it was the largest such program ever carried out and absolutely necessary to save the touristic nature of the area The results have been generally praised Near problems developed in the coast's central part. The situation is tar from redressed in Ostend: trouble spots appeared at the very western end and intensive erosion has occurred in Bredene, near Ostend, a situation already described ten years ago. But it was De Haan (aa. Le Coq-sur-mer) that immediate action became necessary and an apparently successful artificial nourishment has just been completed This paper briefly recapitulates the work undertaken at Knokke-Heist; the proposals made for Ostend describes the present situation in Bredene and provides a detailed account of the completed program at De Haan.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.992 | 0.994 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".