The Use of Artificial Reefs for Recreational Diving
Bibliographic record
Abstract
Scuba diving has become a burgeoning branch of the tourism service. Various activities of recreational diving do not especially necessitate natural reefs-any varied vehicle such as ship, plane and other large structures may be adequately attractive. Coastal groups are turning to these structures by the way of supplying new locations for scuba diving tourists. Despite the lack of a global database, our literature review indicated extensive use of artificial reefs for recreation in the United States, currently viewed as the pioneering puissance and professional in the field. Moreover, the Canadian and Australian governments have both promoted several “ships to reef” programs focused on recreation. However, the used of three-dimensional structures (ships, planes etc.) as artificial reefs in sensitive ecosystems such as the Mediterranean and Red Sea is not a common practice. Although scuba divers are interested in such type of structures, ships to reef is a matter of debate especially in the Mediterranean region. In Turkey, a National Artificial Reef Program was drafted in 2008, however there is no regulation at present about intentionally sinking a ship for the creation of recreational diving destinations. The aim of this review was to investigate the use of man-made structures as artificial reefs for recreational diving around the world.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".