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Record W7104258933 · doi:10.14286/jgz7fm

Quantifying fish-turbine interactions using new high residency acoustic electronic tagging technology

2025· dataset· en· W7104258933 on OpenAlexaffabout

Bibliographic record

VenueOcean Tracking Network · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsOcean Tracking Network
Fundersnot available
KeywordsBayNova scotiaTidal powerPopulationEndangered speciesMarine energyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.320
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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