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Corrigendum to “Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing” [Sleep Health 9 (2023) 596-610]

Sleep Health(2024)10.1016/j.sleh.2023.11.008Source: DataRank Database

Corrigendum to “Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing” [Sleep Health 9 (2023) 596-610] is a research paper published in Sleep Health (2024). On theSindex it has a DataRank of 0. It has been cited 2 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access2 citations

Cite:

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (33 grants)OA: hybridTopics (11)IDs (PubMed, PMC, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (8)

Margeaux M. Schade,Lindsay Master ORCID,Vasant Honavar ORCID,Nicole G. Nahmod ORCID,Anne‐Marie Chang ORCID

Live enrichment

PubMed:38360520 PMC:PMC12341005 OpenAlex:https://openalex.org/W4391848044

National Heart, Lung, and Blood Institute

Grant: N01-HC-95161

National Heart, Lung, and Blood Institute

Grant: R24 HL114473

National Heart, Lung, and Blood Institute

Grant: N01-HC-95169

National Heart, Lung, and Blood Institute

Grant: UL1-TR-001079

National Heart, Lung, and Blood Institute

Grant: N01-HC-95168

National Heart, Lung, and Blood Institute

Grant: N01-HC-95163

National Heart, Lung, and Blood Institute

Grant: N01-HC-95159

National Heart, Lung, and Blood Institute

Grant: N01-HC-95167

National Heart, Lung, and Blood Institute

Grant: N01-HC-95166

National Heart, Lung, and Blood Institute

Grant: N01-HC-95165

National Heart, Lung, and Blood Institute

Grant: UL1-TR-000040

National Heart, Lung, and Blood Institute

Grant: N01-HC-95164

National Heart, Lung, and Blood Institute

Grant: N01-HC-95162

National Heart, Lung, and Blood Institute

Grant: 75N92019R002

National Heart, Lung, and Blood Institute

Grant: N01-HC-95160

National Heart, Lung, and Blood Institute

Grant: HHSN268201500003I

National Heart, Lung, and Blood Institute

Grant: UL1-TR-001420

National Center for Advancing Translational Sciences

Grant: UL1TR002014

National Institute on Aging

Grant: 056250

NHLBI NIH HHS

Grant: N01 HC095169

NHLBI NIH HHS

Grant: N01 HC095160

NHLBI NIH HHS

Grant: N01 HC095162

NHLBI NIH HHS

Grant: N01 HC095167

NHLBI NIH HHS

Grant: N01 HC095159

NHLBI NIH HHS

Grant: N01 HC095168

NHLBI NIH HHS

Grant: N01 HC095164

NHLBI NIH HHS

Grant: N01 HC095166

NIA NIH HHS

Grant: R43 AG056250

NIA NIH HHS

Grant: U2C AG060408

NHLBI NIH HHS

Grant: N01 HC095165

NHLBI NIH HHS

Grant: R01 HL098433

NHLBI NIH HHS

Grant: N01 HC095161

NHLBI NIH HHS

Grant: N01 HC095163

hybridLicense: cc-by

journalhttps://doi.org/10.1016/j.sleh.2023.11.008

publisherhttps://doi.org/10.1016/j.sleh.2023.11.008

publisherhttps://api.elsevier.com/content/article/PII:S2352721823002905?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2352721823002905?httpAccept=text/plain

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38360520

Fields of Study

Sleep and related disordersSleep and Work-Related Fatigue

Keywords

ActigraphySleep (system call)Rest (music)PsychologyComputer scienceMedicineCircadian rhythmNeuroscienceInternal medicine

Sustainable Development Goals

SDG 0: Quality Education