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Record W2606591337

EFFECTS OF ACOUSTIC DISTURBANCE CAUSED BY SHIP TRAFFIC ON COMMON FISH SPECIES IN THE HIGH ARCTIC

2016· article· en· W2606591337 on OpenAlexaboutno aff
Silviya V. Ivanova

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsDisturbance (geology)ArcticFish <Actinopterygii>Environmental scienceFisheryGeographyEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Due to climate change the high Arctic is experiencing growth in acoustic anthropogenic disturbance that may affect aquatic species, such as Arctic cod (Boreogadus saida), and Inuit residents. To our knowledge, no studies have been conducted on this topic and species. Furthermore, there is urgent need for conservation action through much needed collaboration between Inuit and researchers, and an engagement of different audiences, and thus, a documentary film was added to the project as means of communication. Resolute Bay is a small Inuit community located just north of the Northwest Passage, where ships are often visitors in the summer and the bay is a home to Arctic cod, making this the perfect location to address this gap of knowledge and communication. In Chapter 2, we show that Arctic cod was horizontally displaced from its home range and individuals reduced the extent of their habitat use and changed their swimming patterns during vessel presence and movement. In Chapter 3, we describe and put into context the different techniques the film uses to accomplish the set objectives: highlighting the issues facing the Inuit and the arctic ecosystem, the value of Inuit traditional ecological knowledge and need for its incorporation into future studies in the region. Arctic cod spatial distribution and behavioral changes carry consequences for the whole Arctic ecosystem and need to be well understood by scientists as well as by a wide range of audiences to allow for sustainable management and timely conservation action.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.099
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.190
Teacher spread0.171 · 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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