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Record W3006475242

Shared Waters – Southern Resident Killer Whales and Ferries Crossing the Border

2016· article· en· W3006475242 on OpenAlexaboutno aff
Richard D. Huey, Leslie James

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyFisheryGeographyGeologyBiology
DOInot available

Abstract

fetched live from OpenAlex

As members of the ECHO group, British Columbia Ferry Services Inc. (BCF) and Washington State Ferries (WSF) are working together on policy development and in-water noise issues relating to the Southern Resident Killer Whales. Policy Development: In 2015, BCF and Washington State Ferries (WSF) worked together to develop a joint policy and Best Management Practices for whale/ferry encounters. The goal is to coordinate effective whale/ferry encounters given that: The Southern Resident Killer Whale and other species share the same cross-boundary waters, Southern Resident Killer Whale are listed as “species at risk” for both countries, BCF transits U.S. waters (Tsawwassen to Swartz Bay) and WSF transits Canadian waters (Anacortes to Sidney). One policy challenge was how to approach legislative differences between the two countries. For example, U.S. guidelines designate a 200 meter ‘no approach zone’ for vessels, while in Canada it is 100 meters. This policy was the first of its kind for both BCF and WSF, and is the first policy of its kind for ferry operators in Canada and the U.S. This is another step in a series of bi-national efforts to protect the Southern Residents. In-water Noise: WSF has been working with the National Marine Fisheries Service and the University of Washington on in-water noise related to ferry terminal construction projects. WSF has also collected in-water noise data for some of its ferries, and will discuss potential implications based on current U.S. guidelines for in-water noise and its effects on whales and pinnipeds. WSF and BCF are hoping to collect more ferry in-water data that will contribute to a better understanding of their fleets’ acoustic signatures. This could lead to possible operational or design adaptations. Whale Tracking: BCF has been working with Fisheries and Oceans Canada (DFO) to install hydrophones at several key locations. The real time streaming of the underwater acoustic environment from underwater hydrophones will pick up Resident Killer Whale calls identifying when and where the whales are present and also calculate the corresponding level of background acoustic noise.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.018
GPT teacher head0.227
Teacher spread0.209 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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