Evidence map›Paper›PMID 36904786›Full record

ArticleSensors (Basel, Switzerland)2023

Ambient Electromagnetic Radiation as a Predictor of Honey Bee (

Vladimir A Kulyukin, Daniel Coster, Anastasiia Tkachenko, Daniel Hornberger, Aleksey V Kulyukin

Full text read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

5 authors.

Vladimir A KulyukinDepartment of Computer Science, Utah State University, Logan, UT 84322, USA.ORCID 0000-0002-8778-5175
Daniel CosterDepartment of Mathematics and Statistics, Utah State University, Logan, UT 84322, USA.ORCID 0000-0002-4801-5637
Anastasiia TkachenkoDepartment of Computer Science, Utah State University, Logan, UT 84322, USA.
Daniel HornbergerDepartment of Computer Science, Utah State University, Logan, UT 84322, USA.
Aleksey V KulyukinDepartment of Computer Science, Utah State University, Logan, UT 84322, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since bee traffic is a contributing factor to hive health and electromagnetic radiation has a growing presence in the urban milieu, we investigate ambient electromagnetic radiation as a predictor of bee traffic in the hive's vicinity in an urban environment. To that end, we built two multi-sensor stations and deployed them for four and a half months at a private apiary in Logan, UT, USA. to record ambient weather and electromagnetic radiation. We placed two non-invasive video loggers on two hives at the apiary to extract omnidirectional bee motion counts from videos. The time-aligned datasets were used to evaluate 200 linear and 3,703,200 non-linear (random forest and support vector machine) regressors to predict bee motion counts from time, weather, and electromagnetic radiation. In all regressors, electromagnetic radiation was as good a predictor of traffic as weather. Both weather and electromagnetic radiation were better predictors than time. On the 13,412 time-aligned weather, electromagnetic radiation, and bee traffic records, random forest regressors had higher maximum R2 scores and resulted in more energy efficient parameterized grid searches. Both types of regressors were numerically stable.

Indexed as

Conservation of Energy ResourcesWeatherAnimalsBeesMotionPhysical Phenomenaapiary scienceelectromagnetic radiationelectronic beehive monitoringenergy efficiencygrid searchmachine learningpower useprecision apicultureprecision beekeepingregression

Identifiers

PMID36904786
PMCPMC10007012

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table measurements read3
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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.