Evidence map›Paper›PMID 33436710›Full record

ArticleScientific reports2021

An open access dataset for developing automated detectors of Antarctic baleen whale sounds and performance evaluation of two commonly used detectors.

Brian S Miller, IWC-SORP/SOOS Acoustic Trends Working Group, Naysa Balcazar, Sharon Nieukirk, Emmanuelle C Leroy, Meghan Aulich, Fannie W Shabangu, Robert P Dziak, Won Sang Lee, Jong Kuk Hong

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.4field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 35 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 10 institutions in 8 countries.

Brian S MillerAustralian Antarctic Division, 203 Channel Highway, Kingston Tasmania, Australia. brian.miller@aad.gov.au.
IWC-SORP/SOOS Acoustic Trends Working Group
Naysa BalcazarUnaffiiliated, Brisbane, QLD, Australia.
Sharon NieukirkPacific Marine Environmental Laboratory, NOAA, Newport, OR, USA.
Emmanuelle C LeroyUnaffiliated, Bretagne, France.
Meghan AulichCentre for Marine Science and Technology, Curtin University, Bentley, WA, Australia.
Fannie W ShabanguDepartment of Environment, Forestry and Fisheries, Fisheries Management Branch, Cape Town, South Africa.
Robert P DziakPacific Marine Environmental Laboratory, NOAA, Newport, OR, USA.
Won Sang LeeKorea Polar Research Institute, Incheon, 21990, South Korea.
Jong Kuk HongKorea Polar Research Institute, Incheon, 21990, South Korea.
Australian Antarctic Division · AUNOAA Pacific Marine Environmental Laboratory · USAlfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung · DECentre National de la Recherche Scientifique · FRCurtin University · AUKorea Polar Research Institute · KRCape Peninsula University of Technology · ZADepartment of Agriculture, Land Reform and Rural Development · ZATexas A&M University at Galveston · USUniversity of Concepción · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since 2001, hundreds of thousands of hours of underwater acoustic recordings have been made throughout the Southern Ocean south of 60° S. Detailed analysis of the occurrence of marine mammal sounds in these circumpolar recordings could provide novel insights into their ecology, but manual inspection of the entirety of all recordings would be prohibitively time consuming and expensive. Automated signal processing methods have now developed to the point that they can be applied to these data in a cost-effective manner. However training and evaluating the efficacy of these automated signal processing methods still requires a representative annotated library of sounds to identify the true presence and absence of different sound types. This work presents such a library of annotated recordings for the purpose of training and evaluating automated detectors of Antarctic blue and fin whale calls. Creation of the library has focused on the annotation of a representative sample of recordings to ensure that automated algorithms can be developed and tested across a broad range of instruments, locations, environmental conditions, and years. To demonstrate the utility of the library, we characterise the performance of two automated detection algorithms that have been commonly used to detect stereotyped calls of blue and fin whales. The availability of this library will facilitate development of improved detectors for the acoustic presence of Southern Ocean blue and fin whales. It can also be expanded upon to facilitate standardization of subsequent analysis of spatiotemporal trends in call-density of these circumpolar species.

Indexed as

Access to InformationAcousticsAnimalsAntarctic RegionsBalaenopteraDatasets as TopicSignal Processing, Computer-AssistedSound SpectrographySpecies SpecificityVocalization, Animal

Identifiers

PMID33436710
PMCPMC7804014
OpenAlexW3119828875

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.