Evidence map›Paper›PMID 42282717›Full record

ArticlebioRxiv : the preprint server for biology2026

Catch me if you can:

Laura Leventhal, Moises Exposito-Alonso

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

2 authors.

Laura LeventhalDepartment of Biology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-8650-5522
Moises Exposito-AlonsoDepartment of Integrative Biology, University of California Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0001-5711-0700

Funding

Predicting and controlling polygenic health traits using probabilistic models and evolution-inspired gene editingDP5OD029506 · OD · UNIVERSITY OF CALIFORNIA BERKELEY · PI EXPOSITO-ALONSO, MOISES · 2020 to 2024
$2.0M
NIH HHS DP5 OD029506
6 · The paper itself

Abstract

Anthropogenic climate change fosters unprecedented temperature challenges, with each year breaking a temperature record. Through evolution by natural selection, species and their populations have adapted to their previously local environments. However, as the average global land temperature has increased by ~2 °C or more, natural selection on many species may not act fast enough with climate change, creating an adaptation lag. To understand potential adaptation lags to recent climate change, we conducted a meta-analysis on the largest set of single-species field transplantation experiments across climates with the broadly-distributed model plant,

Identifiers

PMID42282717
PMCPMC13252057

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.