Quantifying fish-turbine interactions using new high residency acoustic electronic tagging technology
Bibliographic record
Abstract
This is the OBIS extraction of the Ocean Tracking Network and Acadia University (Acadia U) Quantifying fish-turbine interactions using new high residency acoustic electronic tagging technology, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=HRFORCE).Abstract:The Nova Scotia government has pledged to produce 40% of the provinces electricity from sustainable forms of energy by 2020. This plan includes the development of an instream tidal turbine array in the Bay of Fundy. The Bay of Fundy has the highest tides in the world, making it a prime site for the operation of instream tidal turbines. Extensive environmental monitoring must be performed before the installment of an array to better understand the effect turbines could have on marine species. In 2009, the Fundy Ocean Research Center for Energy was established in Minas Passage, Nova Scotia to test instream tidal turbines. It is unknown whether the installation of turbines in Minas Passage could negatively influence the abundance of fish stocks that inhabit Minas Basin. It is important to know how tidal turbines influence the behavior of all species, but especially those currently federally listed as endangered (e.g., Atlantic salmon), since losses at the individual level could negatively affect the population (i.e. iBOF Atlantic Salmon). Approximately 70 species of fish migrate through Minas Passage to access Minas Basin for feeding. Species abundance estimates are known for a handful of these species, including Gaspereau River Alewife, Shubenacadie River Striped Bass and Saint John River Atlantic Sturgeon. Five species of fish (Atlantic salmon, Atlantic herring, Alewife, Striped bass, and Atlantic Sturgeon) will be tagged with new High Residency (HR) fish tagging technology developed by a local NS company (Vemco). This technology can detect fish in environments with high current speeds (i.e., Minas Passage 6 m/s). The information obtained from the HR tags will be used to determine the effects tidal turbines have at the individual level for endangered species like the Atlantic salmon, and at the population level for species with known population estimates.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".