ArticleNature2019
Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis.
Article in Nature, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed.
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- AI for Accelerated Materials Discovery: From Generative Design to Autonomous Realization.Chemical reviews · 2026Article
- Artificial Intelligence-Guided Discovery of Covalent Organic Frameworks for Next-Generation Polyfluoroalkyl Substances Removal.ACS applied materials & interfaces · 2026Review
- Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning.Journal of the American Chemical Society · 2026Article
- Towards a sustainable high-quality materials data ecosystem: frameworks and strategies.National science review · 2026Review
- Expanding diversity in chemical space.Nature chemistry · 2026Article
- General-Purpose Models for the Chemical Sciences: LLMs and Beyond.Chemical reviews · 2026Review
- Machine learning in next-generation AEM fuel cells: a systematic review.RSC advances · 2026Review
- Text-mined dataset of solid-state syntheses with impurity phases using Large Language Model.Scientific data · 2025Article
- Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models.Angewandte Chemie (International ed. in English) · 2025Article
- Intelligent Systems for Inorganic Nanomaterial Synthesis.Nanomaterials (Basel, Switzerland) · 2025Review
- Spaces of mathematical chemistry.Theory in biosciences = Theorie in den Biowissenschaften · 2024Article
- Unleashing the power of AI in science-key considerations for materials data preparation.Scientific data · 2024Article
- Probing machine learning models based on high throughput experimentation data for the discovery of asymmetric hydrogenation catalysts.Chemical science · 2024Article
- Unified Roadmap for ZIF-8 Nucleation and Growth: Machine Learning Analysis of Synthetic Variables and Their Impact on Particle Size and Morphology.Chemistry of materials : a publication of the American Chemical Society · 2024Article
- Revisiting El-Sayed Synthesis: Bayesian Optimization for Revealing New Insights during the Growth of Gold Nanorods.Chemistry of materials : a publication of the American Chemical Society · 2024Article
- Accelerated chemical science with AI.Digital discovery · 2024Review
- Artificial Intelligence-Powered Electronic Skin.Nature machine intelligence · 2023Article
- Exploiting redundancy in large materials datasets for efficient machine learning with less data.Nature communications · 2023Article
- Assessing Thermodynamic Selectivity of Solid-State Reactions for the Predictive Synthesis of Inorganic Materials.ACS central science · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most chemical experiments are planned by human scientists and therefore are subject to a variety of human cognitive biases
Indexed as
Identifiers
31511682What 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.