ArticleResearch square2026
Machine Learning Models with a Reject Option to Minimize Prediction Error: Application to Optical Properties of Dye Molecules.
Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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Who cites it
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Authors and funding
7 authors.
Funding
Abstract
Predictions of the optical properties of dyes must be exceptionally accurate because even a small prediction error of, for instance, the wavelength can dramatically misrepresent the dye visible color. To address this challenge, we developed a novel model dubbed
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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.