Evidence map›Paper›PMID 42160395›Full record

ArticlePloS one2026

Maximum likelihood estimation of perceptual differences in sorting tasks.

Yulong Liu, Huazhi Li, Yali Xiang, Mengni Zhou, Qingqing Li, Hongtao Yu, Yoshimichi Ejima, Satoshi Takahashi, Jiajia Yang, Bin Bai and 2 more

Abstract read
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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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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

12 authors.

Yulong LiuKey Laboratory of Intelligent Monitoring on Navigation Safety, Hunan University of Information Technology, Changsha, China.ORCID https://orcid.org/0000-0001-5212-6076
Huazhi LiLiaoning Normal University, Liaoning, China.
Yali XiangKey Laboratory of Intelligent Monitoring on Navigation Safety, Hunan University of Information Technology, Changsha, China.
Mengni ZhouCollege of Software, Taiyuan University of Technology, Taiyuan, China.
Qingqing LiSchool of Education, Wenzhou University, Wenzhou, China.
Hongtao YuLiaoning Normal University, Liaoning, China.
Yoshimichi EjimaCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.
Satoshi TakahashiCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.
Jiajia YangCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.
Bin BaiKey Laboratory of Intelligent Monitoring on Navigation Safety, Hunan University of Information Technology, Changsha, China.
Xinian YiKey Laboratory of Intelligent Monitoring on Navigation Safety, Hunan University of Information Technology, Changsha, China.
Jinglong WuCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psychophysical paradigms are foundational for quantifying perceptual discrimination. Yet, a persistent trade-off between assessment efficiency and accuracy limits their broad applicability. To address this, we introduce a novel evaluation model grounded in maximum likelihood estimation (MLE) for perceptual sorting tasks. This work details the model's formulation, validates its performance through simulation, and demonstrates its efficacy in a tactile angle-sorting experiment. Our findings reveal that the sorting paradigm, particularly with five stimuli across three trials, achieves an optimal balance of efficiency and robustness. This method provides a potentially useful and relatively efficient approach for assessing perceptual discriminability within the tactile experimental context, with preliminary indications of its applicability in both research and practical screening.

Indexed as

Discrimination, PsychologicalHumansLikelihood FunctionsPsychophysics

Identifiers

PMID42160395
PMCPMC13189420

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.