Evidence map›Paper›PMID 35299633›Full record

ArticleFrontiers in bioengineering and biotechnology2022

Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties.

Santiago Arroyave-Tobon, Jordan Drapin, Anton Kaniewski, Jean-Marc Linares, Pierre Moretto

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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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.

Santiago Arroyave-TobonInstitut Des Sciences Du Mouvement, Faculté Des Sciences Du Sport, Aix-Marseille Université, CNRS, Marseille, France.
Jordan DrapinCentre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France.
Anton KaniewskiInstitut Des Sciences Du Mouvement, Faculté Des Sciences Du Sport, Aix-Marseille Université, CNRS, Marseille, France.
Jean-Marc LinaresInstitut Des Sciences Du Mouvement, Faculté Des Sciences Du Sport, Aix-Marseille Université, CNRS, Marseille, France.
Pierre MorettoCentre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quadrupeds and hexapods are known by their ability to adapt their locomotive patterns to their functions in the environment. Computational modeling of animal movement can help to better understand the emergence of locomotive patterns and their body dynamics. Although considerable progress has been made in this subject in recent years, the strengths and limitations of kinematic simulations at the scale of small moving animals are not well understood. In response to this, this work evaluated the effects of modeling uncertainties on kinematic simulations at small scale. In order to do so, a multibody model of a

Indexed as

antinverse kinematicsmotion capturemultibodyuncertainty

Identifiers

PMID35299633
PMCPMC8921731

What OpenQuestion holds

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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.