Evidence map›Paper›PMID 37957151›Full record

ArticleScientific data2023

A labeled data set of underwater images of fish and crab species from five mesohabitats in Puget Sound WA USA.

Dara M Farrell, Bridget Ferriss, Beth Sanderson, Karl Veggerby, Lauren Robinson, Anusua Trivedi, Shreyaan Pathak, Sreya Muppalla, Jane Wang, Dan Morris and 1 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Dara M Farrell *University of Washington (UW), School of Aquatic and Fishery Sciences, Seattle, 98195, USA. daraf@uw.edu.ORCID 0000-0002-5662-9938
Bridget Ferriss *Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration (NOAA), 7600 Sand Point Way Northeast, Seattle, 98115, USA.
Beth Sanderson *Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, 98112, USA.
Karl Veggerby *University of Washington (UW), School of Aquatic and Fishery Sciences, Seattle, 98195, USA.
Lauren Robinson *iMerit, 985 University Avenue, Suite 8, Los Gatos, California, 95032, USA.
Anusua Trivedi *Microsoft (MS), Microsoft AI for Good Research Lab, 14820 NE 36th Street, Redmond, Redmond, 98052, Washington, USA.
Shreyaan Pathak *Microsoft (MS), Microsoft AI for Good Research Lab, 14820 NE 36th Street, Redmond, Redmond, 98052, Washington, USA.
Sreya Muppalla *Microsoft (MS), Microsoft AI for Good Research Lab, 14820 NE 36th Street, Redmond, Redmond, 98052, Washington, USA.
Jane Wang *Microsoft (MS), Microsoft AI for Good Research Lab, 14820 NE 36th Street, Redmond, Redmond, 98052, Washington, USA.
Dan Morris *Microsoft (MS), Microsoft AI for Good Research Lab, 14820 NE 36th Street, Redmond, Redmond, 98052, Washington, USA.
Rahul Dodhia *Microsoft (MS), Microsoft AI for Good Research Lab, 14820 NE 36th Street, Redmond, Redmond, 98052, Washington, USA.

Funding

UW | Washington Sea Grant, University of Washington (Washington Sea Grant) UWSC10159
6 · The paper itself

Abstract

The sustainable management of fisheries and aquaculture requires an understanding of how these activities interact with natural fish populations. GoPro cameras were used to collect an underwater video data set on and around shellfish aquaculture farms in an estuary in the NE Pacific from June to August 2017 and June to August 2018 to better understand habitat use by the local fish and crab communities. Images extracted from these videos were labeled to produce a data set that is suitable for use in training computer vision models. The labeled data set contains 77,739 images sampled from the collected video; 67,990 objects (fishes and crustaceans) have been annotated in 30,384 images (the remainder have been annotated as "empty"). The metadata of the data set also indicates whether a physical magenta filter was used during video collection to counteract reduced visibility. These data have the potential to help researchers address system-level and in-depth regional shellfish aquaculture questions related to ecosystem services and shellfish aquaculture interactions.

Indexed as

BrachyuraFishesAnimalsAquacultureEcosystemFisheries

Identifiers

PMID37957151
PMCPMC10643608

What OpenQuestion holds

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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.