Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
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.
2 · The registry
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.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
10 authors.
Zeyu GuanHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Hansheng ZhuHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Yaoxin LiHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Yuanzhenzi LuHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Haifeng BuHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Bo XuHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Zhengxu ZhuHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China.
Shengchun ShenHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China. scshen@ustc.edu.cn.ORCID http://orcid.org/0000-0002-7307-2473
Yuewei YinHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China. yyw@ustc.edu.cn.ORCID http://orcid.org/0000-0003-0965-4951
Xiaoguang LiHefei National Research Center for Physical Sciences at the Microscale, Department of Physics, University of Science and Technology of China, Hefei, China. lixg@ustc.edu.cn.ORCID http://orcid.org/0000-0003-4016-4483
Funding
National Natural Science Foundation of China (National Science Foundation of China) 52125204, 52521006National Natural Science Foundation of China (National Science Foundation of China) 52422209National Natural Science Foundation of China (National Science Foundation of China) U21A2066, U25A20231
6 · The paper itself
Abstract
Probabilistic neural networks are good at solving complex optimization tasks, but require stochastic, energy-efficient probabilistic bit (p-bit) neurons and reliable artificial synapses. Here we show stochastic ferroelectric tunnel junctions (s-FTJs) and reliable-FTJs (r-FTJs) by tuning the oxygen vacancy concentration in Hf
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.
Probabilistic computing utilizing HfO · full record | OpenQuestion