ComProScanner/CITATION.cff at main · slimeslab/ComProScanner · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
cff-version: "1.2.0"
authors:
  - family-names: Roy
    given-names: Aritra
    orcid: "https://orcid.org/0000-0003-0243-9124"
  - family-names: Grisan
    given-names: Enrico
    orcid: "https://orcid.org/0000-0002-7365-5652"
  - family-names: Buckeridge
    given-names: John
    orcid: "https://orcid.org/0000-0002-2537-5082"
  - family-names: Gattinoni
    given-names: Chiara
    orcid: "https://orcid.org/0000-0002-3376-6374"
contact:
  - family-names: Roy
    given-names: Aritra
    orcid: "https://orcid.org/0000-0002-4928-2935"
message: If you use this software, please cite our article on arXiv.
preferred-citation:
  authors:
    - family-names: Roy
      given-names: Aritra
      orcid: "https://orcid.org/0000-0003-0243-9124"
    - family-names: Grisan
      given-names: Enrico
      orcid: "https://orcid.org/0000-0002-7365-5652"
    - family-names: Buckeridge
      given-names: John
      orcid: "https://orcid.org/0000-0002-2537-5082"
    - family-names: Gattinoni
      given-names: Chiara
      orcid: "https://orcid.org/0000-0002-3376-6374"
  date-published: 2025-10-23
  identifiers:
    - type: other
      value: "arXiv:2510.20362"
      description: "arXiv preprint"
  title: "ComProScanner: A multi-agent based framework for composition-property structured data extraction from scientific literature"
  type: article
  url: "https://arxiv.org/abs/2510.20362"
repository-code: "https://github.com/slimeslab/ComProScanner"
license: MIT
title: "ComProScanner: A multi-agent based framework for composition-property structured data extraction from scientific literature"
type: software
url: "https://slimeslab.github.io/ComProScanner/"
version: "0.1.4"
date-released: 2025-12-03
keywords:
  - materials science
  - data extraction
  - multi-agent systems
  - machine learning
  - computational materials science
  - text mining
  - composition-property database