Administration of EU (+ FTA) and other Fleets Involved in Aquaculture of Salmonids
Bibliographic record
Abstract
t is widely acknowledged that there exists a dearth of information with regard to fleet involved in aquaculture of salmonids. To address this insufficiency, and to understand the gaps and grey areas, Transport Canada funded a project in 2017 that aimed to gain an in-depth understanding of how the Norwegian, Irish, Chile and Australian fleet involved in aquaculture of salmonids are registered and administered. The World Maritime University undertook the project, and contracted external consultants to develop and deliver reports from a number of the aforementioned jurisdictions. The project report provides a deep insight into the regulatory framework for the registration of vessels involved in Aquaculture of salmonids. In addition, the areas of operation of these vessels, the safe manning procedures and the framework for the protection of the marine environment from vessels involved in aquaculture of salmonids has been thoroughly examined within the ambit of the report. The sample of the study is based upon both primary sources and secondary sources of law, as well as explanations and rational interpretations provided by respondents interviewed. The scope of “vessels” included all vessels that support the aquaculture salmonids industry, including fish delousing, feed barges/ships, well vessels, live fish carriers, pen repair and monitoring vessels, ROV support vessels.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".