Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning-Assisted Analysis of Small Angle X-ray Scattering   Small angle X-ray scattering (SAXS) is extensively used in materials science
as a way of examining nanostructures. The analysis of experimental SAXS data
involves mapping a rather simple data format to a vast amount of structural
models. Despite various scientific computing tools to assist the model
selection, the activity heavily relies on the SAXS analysts' experience, which
is recognized as an efficiency bottleneck by the community. To cope with this
decision-making problem, we develop and evaluate the open-source, Machine
Learning-based tool SCAN (SCattering Ai aNalysis) to provide recommendations on
model selection. SCAN exploits multiple machine learning algorithms and uses
models and a simulation tool implemented in the SasView package for generating
a well defined set of datasets. Our evaluation shows that SCAN delivers an
overall accuracy of 95%-97%. The XGBoost Classifier has been identified as the
most accurate method with a good balance between accuracy and training time.
With eleven predefined structural models for common nanostructures and an easy
draw-drop function to expand the number and types training models, SCAN can
accelerate the SAXS data analysis workflow.

2
The categories of this paper are: math
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ