Evidence map›Paper›PMID 40880750›Full record

ArticleNuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment2023

Autonomous screening of complex phase spaces using Bayesian optimization for SAXS measurements.

Khaled Younes, Michael Poli, Priyanka Muhunthan, Ivan Rajkovic, Stefano Ermon, Thomas M Weiss, Matthias Ihme

Abstract read
In one paragraph

Article in Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

7 authors.

Khaled YounesDepartment of Mechanical Engineering, Stanford University, Stanford, CA 94305, United States.ORCID 0000-0001-9562-0963
Michael PoliDepartment of Computer Science, Stanford University, Stanford, CA 94305, United States.
Priyanka MuhunthanDepartment of Mechanical Engineering, Stanford University, Stanford, CA 94305, United States.
Ivan RajkovicSLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource, Menlo Park, CA 94025, United States.
Stefano ErmonDepartment of Computer Science, Stanford University, Stanford, CA 94305, United States.
Thomas M WeissSLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource, Menlo Park, CA 94025, United States.
Matthias IhmeDepartment of Mechanical Engineering, Stanford University, Stanford, CA 94305, United States.

Funding

A Synchrotron Radiation Structural Biology ResourcesP30GM133894 · NIGMS · STANFORD UNIVERSITY · PI Ritimukta Sarangi · 2020 to 2026
$43.3M
NIGMS NIH HHS P30 GM133894
6 · The paper itself

Abstract

The advent of modern, ultrafast X-ray experiments has enabled scientists to probe physical phenomena at an ever smaller scale. However, this has come at a cost of excessive data generation, to the point where current storage and hardware capabilities are routinely surpassed. As such, handling the data efficiently and selectively storing only the information of most relevance is crucial. In this paper, we propose to use Bayesian optimization as a method to alleviate this problem. We apply the method to locate global features in Small Angle X-ray Scattering spectra obtained from conducting experiments with supercritical CO

Indexed as

Bayesian optimizationonline screeningphase space samplingSAXSsupercritical fluids

Identifiers

PMID40880750
PMCPMC12382457

What OpenQuestion holds

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Registered trials

None linked

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.