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Record W7079515200 · doi:10.26108/zmz9-j449

Acoustic hydrophone (icListen) deployed on an Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) to measure habitat specific noise in the Minas Basin, Nova Scotia

2013· article· en· W7079515200 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2013
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsPorpoiseHydrophoneNoise (video)Nova scotiaSound (geography)Ambient noise levelUnderwaterSound pressureTelemetryMooring

Abstract

fetched live from OpenAlex

Electronic tags attached to marine mammals and fish have been developed to sample temperature, pressure (depth), and location. Currently, no tag contains a built in broadband acoustic hydrophone. In this project, as a proof of concept, we attached a full-size high frequency 200 kHz 24-bit smart hydrophone (icListen) to an Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) in order to measure ambient noise from the Minas Basin, Nova Scotia. The front end of the icListen hydrophone was secured to the Atlantic sturgeon through use of a Velcro strap that went around its abdomen, behind the pectoral fins. A line of dissolving suture thread, which passed through a dorsal scute, secured the back end of the icListen to the fish. A V13P acoustic tag glued to the exterior of the icListen was used to track the bioprobe with a VR100 manual tracking unit. Three galvanic releases built into the design corroded after approximately seven hours and released the icListen from the fish. Syntactic foam allowed the icListen to float vertically at the surface and a Single Position Only Tag (SPOT-100) then transmitted location signals to the ARGOS satellite system to direct researchers attempting to retrieve the icListen. Approximately eight hours of acoustic data was collected by the icListen hydrophone during its deployment. Ambient noise was recorded, including a splash upon release, shrimp snapping, boat engine noise, waves, harbour porpoise clicks, and signals from Vemco acoustic transmitters implanted within other fish. Echolocation clicks from a harbour porpoise (Phocoena phocoena) were recorded by the icListen during two separate interactions, both indicating a possible attempt at communication with an acoustic tag. Ten acoustic transmitters were picked up by the VR100; five from Atlantic sturgeon tagged between 2010 and 2012, and five others from striped bass (Morone saxatilis) tagged in 2012. The VR100 identified the IDs of uniquely coded tags, provided a time and location stamp for detections and recorded pressure (depth) readings from some tags. This study provided proof of concept for the deployment of an icListen hydrophone on a marine bioprobe in order to record ambient acoustic data. Insight into the interactions between marine mammals and acoustically tagged fish was gained, and tag data allowed a rough estimate of untagged Atlantic sturgeon to be calculated for the study site, off Kingsport, Nova Scotia.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.231
Teacher spread0.207 · 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
Published2013
Admission routes1
Has abstractyes

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