Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analysis of the first Genetic Engineering Attribution Challenge   The ability to identify the designer of engineered biological sequences --
termed genetic engineering attribution (GEA) -- would help ensure due credit
for biotechnological innovation, while holding designers accountable to the
communities they affect. Here, we present the results of the first Genetic
Engineering Attribution Challenge, a public data-science competition to advance
GEA. Top-scoring teams dramatically outperformed previous models at identifying
the true lab-of-origin of engineered sequences, including an increase in top-1
and top-10 accuracy of 10 percentage points. A simple ensemble of prizewinning
models further increased performance. New metrics, designed to assess a model's
ability to confidently exclude candidate labs, also showed major improvements,
especially for the ensemble. Most winning teams adopted CNN-based
machine-learning approaches; however, one team achieved very high accuracy with
an extremely fast neural-network-free approach. Future work, including future
competitions, should further explore a wide diversity of approaches for
bringing GEA technology into practical use.

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The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin