Evidence map›Paper›PMID 42775638›Full record

ArticleeLife2026

Machine learning of honey bee olfactory behavior identifies repellent odorants in free-flying bees in the field.

Joel Kowalewski, Barbara F Baer-Imhoof, Tom Guda, Matthew Luy, Payton DePalma, Boris Baer, Anandasankar Ray

Abstract read
In one paragraph

Article in eLife, 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

7 authors.

Joel Kowalewski *Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, United States.ORCID https://orcid.org/0000-0002-7060-7890
Barbara F Baer-Imhoof *Department of Entomology, Centre for Integrative Bee Research (CIBER), University of California, Riverside, Riverside, United States.ORCID https://orcid.org/0000-0002-6169-3686
Tom GudaDepartment of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, United States.
Matthew LuyDepartment of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, United States.
Payton DePalmaInterdepartmental Neuroscience Program, University of California, Riverside, Riverside, United States.
Boris BaerDepartment of Entomology, Centre for Integrative Bee Research (CIBER), University of California, Riverside, Riverside, United States.ORCID https://orcid.org/0000-0002-1136-5967
Anandasankar RayDepartment of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, United States.ORCID https://orcid.org/0000-0003-4133-2581

Funding

CARA-California Research Alliance by BASF AU001120
6 · The paper itself

Abstract

Preventing beneficial insects like honey bees (

Indexed as

Behavior, AnimalInsect RepellentsMachine LearningOdorantsSmellAnimalsBeesPredictive Learning ModelsInsect Repellentsapis melliferabehaviorD. melanogasterecologyhoney beemachine learningneuroscienceolfactionrepellent

Identifiers

PMID42775638
PMCPMC13600694

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.