Bibliographic record
Abstract
Dredging is an economically essential activity to most countries, but it also has the potential to have a variety of negative effects on marine flora and fauna. To regulate these potential impacts, International Conventions have been set up which realise the importance of properly managing the disposal of dredged material. In this paper the International Conventions are reviewed, with special attention to the Draft 1996 Protocol to the London Convention of 1972, which includes the Dredged Material Assessment Framework (DMAF) and an explanation of the so-called “reverse list”. It also reviews the Oslo and Paris Convention (the OSPAR) recently revised in 1992. National and regional requirements derived from these, as well as assessment procedures and monitoring programmes are also described. This paper was originally published in Environmental Aspects of Dredging, Proceedings of the CEDA-EuDA Seminar held in conjunction with the PIANC International Conference on Inland and Maritime Navigation and Coastal Problems of East European Countries, at the Technical University of Gdansk, Poland, September 1996. It is reprinted here in a revised and updated version with permission. This subject is further elaborated in a recently published book by Mr Burt and Ms Fletcher, Guide 2: Conventions, Codes and Conditions, Marine Disposal and Land Disposal, reviewed on pages 14-15 of this issue.
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 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.009 | 0.004 |
| Insufficient payload (model declined to judge) | 0.991 | 0.993 |
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".