ArticleACS central science2025
Challenging Reaction Prediction Models to Generalize to Novel Chemistry.
Article in ACS central science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- AI-Driven Synthesis in Medicinal Chemistry: Integrating Large Language Models, Robotic Automation, and Sustainability Metrics to Accelerate Drug Discovery.Medicinal research reviews · 2026Review
- Yield Smarter, Not Harder: Good Practices for Machine Learning of Reaction Outcomes.Journal of the American Chemical Society · 2026Article
- Quantifying the failure modes of current one-step retrosynthesis models.Chemical science · 2026Article
- Stereoselective Biotransformation: Transfer of Learning to Advance Drug Metabolism and Biocatalysis.Angewandte Chemie (International ed. in English) · 2026Review
- The consolidation of open-source computer-assisted chemical synthesis data into a comprehensive database.Journal of cheminformatics · 2025Article
- GoFlow: efficient transition state geometry prediction with flow matching and E(3)-equivariant neural networks.Digital discovery · 2025Article
- Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.Briefings in bioinformatics · 2025Review
- Article
- Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey.Journal of chemical information and modeling · 2025Review
- Computational tools for the prediction of site- and regioselectivity of organic reactions.Chemical science · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning models for anticipating the products of organic reactions have found many use cases, including validating retrosynthetic pathways and constraining synthesis-based molecular design tools. Despite compelling performance on popular benchmark tasks, strange and erroneous predictions sometimes ensue when using these models in practice. The core issue is that common benchmarks test models in an
Identifiers
What OpenQuestion holds
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.