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Early estimation of life expectancy using weekly deaths data

Lanzieri, G.

2023-08-16 public and global health
10.1101/2023.08.11.23293993 medRxiv
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Withdrawal StatementThe author has withdrawn this manuscript owing to the results changing in the final published version, which is now available from Eurostat (see DOI: 10.2785/655566). Therefore, the author does not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 4%
31.0%
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2
Journal of Public Health
◐ 24 papers in training set
Top 0.1%
6.2%
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3
BMC Medical Research Methodology
○ 47 papers in training set
Top 0.2%
5.1%
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4
Scientific Reports
○ 3612 papers in training set
Top 25%
4.0%
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5
Biology Methods and Protocols
◐ 61 papers in training set
Top 0.2%
4.0%
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50% of probability mass above
6
BMJ Open
● 601 papers in training set
Top 6%
3.4%
7
Frontiers in Public Health
○ 148 papers in training set
Top 2%
3.2%
8
International Journal of Environmental Research and Public Health
○ 128 papers in training set
Top 2%
2.6%
9
European Journal of Public Health
◐ 21 papers in training set
Top 0.1%
2.4%
10
Royal Society Open Science
● 214 papers in training set
Top 2%
2.4%
11
Demographic Research
● 11 papers in training set
Top 0.1%
2.1%
12
Frontiers in Artificial Intelligence
○ 20 papers in training set
Top 0.2%
2.0%
13
Journal of Clinical Epidemiology
○ 31 papers in training set
Top 0.5%
1.5%
14
International Journal of Epidemiology
◐ 88 papers in training set
Top 0.9%
1.5%
15
International Journal of Molecular Sciences
○ 494 papers in training set
Top 9%
1.4%
16
Epidemiology and Infection
◐ 89 papers in training set
Top 2%
1.3%
17
European Journal of Epidemiology
○ 43 papers in training set
Top 0.5%
1.3%
18
Vaccines
○ 198 papers in training set
Top 3%
1.1%
19
BMJ Global Health
● 113 papers in training set
Top 2%
1.1%
20
BMC Public Health
○ 158 papers in training set
Top 4%
1.0%
21
BMJ Public Health
● 25 papers in training set
Top 1%
0.8%
22
Scientific Data
○ 209 papers in training set
Top 3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.