PubMed analysis: code and data
Home Page: http://nsaunders.wordpress.com/2010/11/30/analysis-of-retractions-in-pubmed/
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I think you should add "has abstract"[FILTER] to the PubMed queries for the "novel" findings. For example, in 1974 only 5% of citations have abstracts compared to 86% in 2014.
Issue with date display as of 2020-09-01.
As of 2020-09-01 the cumulative timeline charts show incorrect counts for early years.
Hi Neil, I am a bit stumped and would really appreciate your advice.
I followed your code to get the xml file, but for some reason, that file cannot be read using read_xml function due to some encoding issue.
Did you do some processing to the xml file before using it for the journalsToCSV function? If i downloaded the sample xml file that you provided, I did not encounter this issue.
This is the error:
Error in doc_parse_file(con, encoding = encoding, as_html = as_html, options = options) :
Input is not proper UTF-8, indicate encoding !
Bytes: 0xA0 0x6D 0x6F 0x73 [9]
Thanks!
Only showing one bar, with the journal Nature, for some reason.
The issue here is too many queries.
One possible solution goes something like:
journals_cnt <- journals_cnt %>% mutate(journal = paste0(journal, "[JOUR]"))
q <- journals_cnt %>% pull(journal) %>% paste(collapse = " OR ")
es <- entrez_search("pubmed", q)
x <- read_xml(as(es$file), "character")
Problem with this is that the query will be too large, so need to figure out Web history with rentrez.
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