Evidence map›Paper›PMID 30872489›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Reply to Laing et al.: Accurate prediction of circadian time across platforms.

Rosemary Braun, William L Kath, Marta Iwanaszko, Elzbieta Kula-Eversole, Sabra M Abbott, Kathryn J Reid, Phyllis C Zee, Ravi Allada

Abstract readLetterComment
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. HairTime: A noninvasive assay for estimating circadian phase from a single hair sample.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Platform-independent estimation of human physiological time from single blood samples.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Machine learning estimation of human body time using metabolomic profiling.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  6. Article
  7. Review
  8. Assessment of Circadian Rhythms.Neurologic clinics · 2019
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Rosemary BraunBiostatistics Division, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611; rbraun@northwestern.edu.ORCID 0000-0001-9668-9866
William L KathDepartment of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208.
Marta IwanaszkoBiostatistics Division, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.ORCID 0000-0001-6909-5931
Elzbieta Kula-EversoleDepartment of Neurobiology, Northwestern University, Evanston, IL 60208.
Sabra M AbbottDepartment of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.
Kathryn J ReidDepartment of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.
Phyllis C ZeeDepartment of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.
Ravi AlladaDepartment of Neurobiology, Northwestern University, Evanston, IL 60208.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Circadian RhythmGene Expression

Identifiers

PMID30872489
PMCPMC6431220

What OpenQuestion holds

Textmetadata
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.