Evidence map›Paper›PMID 41283409›Full record

ArticleJournal of eye movement research2025

BEACH-Gaze: Supporting Descriptive and Predictive Gaze Analytics in the Era of Artificial Intelligence and Advanced Data Science.

Bo Fu, Kayla Chu, Angelo Ryan Soriano, Peter Gatsby, Nicolas Guardado Guardado, Ashley Jones, Matthew Halderman

Abstract read
In one paragraph

Article in Journal of eye movement research, 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

7 authors.

Bo FuComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.ORCID 0000-0001-9874-9551
Kayla ChuComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.
Angelo Ryan SorianoComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.
Peter GatsbyComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.
Nicolas Guardado GuardadoComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.
Ashley JonesComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.
Matthew HaldermanComputer Engineering and Computer Science, California State University Long Beach, Long Beach, CA 90840, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent breakthroughs in machine learning, artificial intelligence, and the emergence of large datasets have made the integration of eye tracking increasingly feasible not only in computing but also in many other disciplines to accelerate innovation and scientific discovery. These transformative changes often depend on intelligently analyzing and interpreting gaze data, which demand a substantial technical background. Overcoming these technical barriers has remained an obstacle to the broader adoption of eye tracking technologies in certain communities. In an effort to increase accessibility that potentially empowers a broader community of researchers and practitioners to leverage eye tracking, this paper presents an open-source software platform:

Indexed as

eye trackinggaze analyticshuman computer interactionsoftware and engineering

Identifiers

PMID41283409
PMCPMC12641676

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.