Yukon artificial reef monitoring project. Data collection using volunteer research divers
Bibliographic record
Abstract
The San Diego Oceans Foundation sank the HMCS Yukon in 100 feet of water, 1.85 miles off Mission Beach, California as a haven for sea life, an attraction for scuba divers, a platform for environmental education, and a research site for marine scientists. Commissioned in 1963 as a Canadian Mackenzie-class destroyer escort, the HMCS Yukon was towed out to the site to be scuttled. Unfortunately, the HMCS Yukon sank prematurely on July 14, 2000. Monitoring the Yukon is an essential part of its creation as an artificial reef. Without proper study and evaluation, we have no way to accurately assess the impacts of this new reef. Are new fish populations being created increasing the number of these species overall, or is the reef only attracting and concentrating fish from other areas? Because artificial reefs may have a strong negative impact, data is needed to make valid judgments to lay controversy to rest. The main objective of this study is to determine the rate of colonization by fishes, invertebrates, and plants and to determine whether fish remain resident or if they travel between reefs.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".