Evidence map›Paper›PMID 41036246›Full record

ArticleHardwareX2025

RAMM: A Robotic, Autonomous Magnetic field Mapper.

Shinjer Li, Samuel J Rubin, Tyler Meldrum

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in HardwareX, 2025. 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

3 authors.

Shinjer LiWilliam & Mary, Department of Chemistry, 540 Landrum Drive, Williamsburg, VA 23188, USA.
Samuel J RubinWilliam & Mary, Department of Chemistry, 540 Landrum Drive, Williamsburg, VA 23188, USA.
Tyler MeldrumWilliam & Mary, Department of Chemistry, 540 Landrum Drive, Williamsburg, VA 23188, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate spatial mapping of magnetic fields is crucial for a range of scientific, industrial, and medical magnetic devices. Here, we present RAMM: a Robotic, Autonomous Magnetic field Mapper. RAMM consists of a delta-style 3D robot coupled with a three-axis Hall sensor that is able to measure magnetic fields accurately and at relatively low cost. In addition, RAMM is programmatically controlled via a Python interface, facilitating volumetric measurement of

Indexed as

Magnetic fieldOpen-sourceRobotSpatial mapping

Identifiers

PMID41036246
PMCPMC12481935

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.