Evidence map›Paper›PMID 30643215›Full record

ArticleNature methods2019

idtracker.ai: tracking all individuals in small or large collectives of unmarked animals.

Francisco Romero-Ferrero, Mattia G Bergomi, Robert C Hinz, Francisco J H Heras, Gonzalo G de Polavieja

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 158 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
158citing 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

158 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  4. Distinct Swimming Behaviours in Pupae ofEcology and evolution · 2026
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98 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Francisco Romero-FerreroChampalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal.ORCID http://orcid.org/0000-0002-4353-7997
Mattia G BergomiChampalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal.ORCID http://orcid.org/0000-0002-3732-3108
Robert C HinzChampalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal.
Francisco J H HerasChampalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal.
Gonzalo G de PolaviejaChampalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal. gonzalo.polavieja@neuro.fchampalimaud.org.ORCID http://orcid.org/0000-0001-5359-3426

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding of animal collectives is limited by the ability to track each individual. We describe an algorithm and software that extract all trajectories from video, with high identification accuracy for collectives of up to 100 individuals. idtracker.ai uses two convolutional networks: one that detects when animals touch or cross and another for animal identification. The tool is trained with a protocol that adapts to video conditions and tracking difficulty.

Indexed as

Behavior, AnimalSoftwareAlgorithmsAnimalsComputer GraphicsComputer SystemsDrosophilaImage Processing, Computer-AssistedNeuronsProbabilityProgramming LanguagesReference ValuesRegression AnalysisUser-Computer InterfaceVideo RecordingZebrafish

Identifiers

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.