ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Interpretable Machine-Learning and Big Data Mining to Predict the CO
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Emerging Trends in Polymer Chemistry and Materials: From Sustainable Design to Advanced Applications.Materials (Basel, Switzerland) · 2026Article
- Hierarchical Embedded Sphere Model: An Interpretable ML-Guided Multiscale Descriptor Engineering Decodes OER Activity on TM@MOAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Discovering metal-organic framework/polymer mixed-matrix membranes via machine learning for COCommunications materials · 2026Article
- Inverse Design of Metal-Organic Frameworks for CHAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Machine Learning in the Design and Performance Prediction of Organic Framework Membranes: Methodologies, Applications, and Industrial Prospects.Membranes · 2025Review
- Interpretable Machine-Learning and Big Data Mining to Predict the COAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Mixed matrix membranes (MMMs) are renowned for their exceptional gas separation capabilities. In this work, high-throughput computing screening and machine learning are employed to evaluate the CO
Indexed as
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.