Evidence map›Paper›PMID 40925556›Full record

ArticleJournal of the Royal Society, Interface2025

Single camera estimation of microswimmer depth with a convolutional network.

Ali Hosseini, Célia Fosse, Maya Awada, Marcel Stimberg, Romain Brette

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Ali Hosseini *Institute of Intelligent Systems and Robotics, Sorbonne Université, Paris, Île-de-France, France.
Célia Fosse *Institute of Intelligent Systems and Robotics, Sorbonne Université, Paris, Île-de-France, France.
Maya AwadaInstitute of Intelligent Systems and Robotics, Sorbonne Université, Paris, Île-de-France, France.
Marcel StimbergInstitute of Intelligent Systems and Robotics, Sorbonne Université, Paris, Île-de-France, France.
Romain BretteInstitute of Intelligent Systems and Robotics, Sorbonne Université, Paris, Île-de-France, France.ORCID 0000-0003-0110-1623

Funding

Agence Nationale de la Recherche
6 · The paper itself

Abstract

A number of techniques have been developed to measure the three-dimensional trajectories of protists, which require special experimental set-ups, such as a pair of orthogonal cameras. On the other hand, machine learning techniques have been used to estimate the vertical position of spherical particles from the defocus pattern, but they require the acquisition of a labelled dataset with finely spaced vertical positions. Here, we describe a simple way to make a dataset of

Indexed as

Machine LearningNeural Networks, ComputerParameciumimage analysismachine learningmicroscopymicroswimmerprotisttracking

Identifiers

PMID40925556
PMCPMC12419879

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.