ArticleScientific data2025
A Standardized Semantic Feature Norm for 954 Cantonese Concepts.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
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Who cites it
1 citing paper in PubMed.
- Estimating sample size in conceptual property norms by standardizing coverage.Behavior research methods · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
This study established psycholinguistic norms on Cantonese conceptual semantic features (CanFeat) with 954 concepts and semantic features, including feature frequency, sharing degree, and type of each feature. We provided concept-level variables, including participant count, feature counts (total, distinct, concept-specific, concept-shared), feature proportions, coverage, category labels (superordinate category and subordinate category), familiarity, and concreteness. We validated the reliability, specificity, and categorical structural consistency of the dataset through multiple analyses, including intra-coder reliability checks, gender comparability assessments, semantic category distinctions, and feature-level comparisons with established norms. We also compared CanFeat with norms in other languages, highlighting both similarities and differences. The present norming offers a timely and valuable resource for researchers in psycholinguistics, particularly those focusing on Cantonese production and semantic representation.
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Registered trials
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.