Evidence map›Paper›PMID 38464748›Full record

ArticlePeerJ2024

High-resolution density assessment assisted by deep learning of

Alberto Gayá-Vilar, Adolfo Cobo, Alberto Abad-Uribarren, Augusto Rodríguez, Sergio Sierra, Sabrina Clemente, Elena Prado

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Alberto Gayá-VilarDepartment of Animal Biology, Soil and Geology, University of La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain.
Adolfo CoboPhotonics Engineering Group, University of Cantabria, Santander, Cantabria, Spain.
Alberto Abad-UribarrenSantander Oceanographic Center, Spanish Institute of Oceanography (IEO-CSIC), Santander, Cantabria, Spain.
Augusto RodríguezSantander Oceanographic Center, Spanish Institute of Oceanography (IEO-CSIC), Santander, Cantabria, Spain.ORCID 0000-0002-4626-3194
Sergio SierraComplutum Geographic Information Technologies (COMPLUTIG), Alcalá de Henares, Madrid, Spain.
Sabrina ClementeDepartment of Animal Biology, Soil and Geology, University of La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain.
Elena PradoSantander Oceanographic Center, Spanish Institute of Oceanography (IEO-CSIC), Santander, Cantabria, Spain.

Funding

Biodiversity Foundation of the Ministry for the Ecological Transition and the Demographic ChallengeEuropean Union’s LIFE program
6 · The paper itself

Abstract

This study presents a novel approach to high-resolution density distribution mapping of two key species of the 1170 "Reefs" habitat,

Indexed as

Deep LearningEcosystemBaysSpainArtificial intelligenceHabitat mappingNatura 2000 networkObject detection modelVulnerable marine ecosystem

Identifiers

PMID38464748
PMCPMC10924775

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.