Evidence map›Paper›PMID 37503196›Full record

ArticlebioRxiv : the preprint server for biology2023

Evaluating evidence for co-geography in the

Clara T Rehmann, Peter L Ralph, Andrew D Kern

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Clara T RehmannUniversity of Oregon, Institute of Ecology and Evolution and Department of Biology.ORCID 0009-0006-3475-3053
Peter L RalphUniversity of Oregon, Institute of Ecology and Evolution and Department of Biology.ORCID 0000-0002-9459-6866
Andrew D KernUniversity of Oregon, Institute of Ecology and Evolution and Department of Biology.ORCID 0000-0003-4381-4680
University of Oregon · US

Funding

Deep learning for population geneticsR01HG010774 · NHGRI · UNIVERSITY OF OREGON · PI ANDREW D KERN · 2020 to 2026
$3.2M
Computational Population GeneticsR35GM148253 · NIGMS · UNIVERSITY OF OREGON · PI ANDREW D KERN · 2023 to 2026
$1.5M
NHGRI NIH HHS R01 HG010774NIGMS NIH HHS R35 GM148253
6 · The paper itself

Abstract

The often tight association between parasites and their hosts means that under certain scenarios, the evolutionary histories of the two species can become closely coupled both through time and across space. Using spatial genetic inference, we identify a potential signal of common dispersal patterns in the

Identifiers

PMID37503196
PMCPMC10370088
OpenAlexW4384697431

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.