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Updated: Jun 3, 2026

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets
Published on: March 1, 2024
The Target Confusability Competition ensemble model predicts full feature distribution reports
Timothy F Brady1, Chattarin Poungtubtim2, Maria M Robinson3
1Department of Psychology, University of California San Diego, La Jolla, CA, USA. tfbrady@ucsd.edu.
Abstract:
Khvostov et al. (Psychonomic Bulletin & Review 32: 2903-2912, 2025) present compelling evidence that observers have explicit access to detailed ensemble feature distributions, challenging the traditional view that only summary statistics are available. Here, we demonstrate that the Target Confusability Competition (TCC) ensemble model (Robinson & Brady, Nature Human Behaviour, 7: 1638-1651, 2023) provides a straightforward process-level account of these results. Without any parameter tuning, the model accurately predicts the observed response patterns across Gaussian, uniform, and bimodal color distributions. This alignment underscores the utility of TCC-ensemble in explaining ensemble perception and highlights the value of similarity-based encoding and integration mechanisms in supporting access to distributional structure.
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