Comments (5)
searching with dictionaries
cd CEVOpen
verify that oil186
is a subdirectory
ls oil186
then search:
ami-search -p oil186 --dictionary species country mydictionaries/instrument.xml
species
is a builtin search, country
is a builtin dictionary, mydictionaries/instrument.xml
is relative to current directory.
Results are in PMC*/results/search/instrument/results.xml
etc.
and aggregated in
/some/where/.../CEVOpen/oil186/search.instrument.snippets.xml
as
<projectSnippetsTree>
<snippetsTree>
<snippets file="oil186/PMC4391421/results/search/instrument/results.xml">
<result pre="Ph. Eur. 5.0 [ 3 ], by using a modified" exact="Clevenger" post="apparatus (with the EO collection area cooled to prevent"/>
<result pre="chromatography-mass spectrometry. Samples were analyzed by gas chromatography using a" exact="HP6890" post="instrument coupled with a HP 5973 mass spectrometer. The"/>
</snippets>
</snippetsTree>
<snippetsTree>
<snippets file="oil186/PMC5080681/results/search/instrument/results.xml">
<result pre="500 ml deionized water. Then, the flask was connected with" exact="Clevenger" post="apparatus, which was placed in the same apparatus. While"/>
<result pre="the fresh weight. GC-MS analysis GC-MS chromatograms were recorded using" exact="Shimadzu" post="QP-5000 GC-MS. The GC was equipped with Rtx-5 ms"/>
<result pre="fresh weight. GC-MS analysis GC-MS chromatograms were recorded using Shimadzu" exact="QP-5000" post="GC-MS. The GC was equipped with Rtx-5 ms column"/>
</snippets>
</snippetsTree>
Each CTree (PMC document) is searched into snippetsTree
and the result
XML element is
in W3C Annotation format (pre
, exact
, post
)
from cevopen.
Simple grep
that finds mass spec:
grep -r -E -o ".{0,50}mass spectromet{0,50}" PMC*/scholarly.html
will search all the HTML for "mass spectrom" and gives 50 characters either side
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Hello,
I am working on how to migrate the article/instrument matches to Wikidata.
The xml with the excerpts is fantastic, but my xml processing skills are still incipient. I remember having seen in the sprint a summary table with the PMC IDs in one column and counts for each term in another column.
Would you know how I can obtain this summary file?
EDIT: Even though I'm still not able to generate the full html table, I could draft some code to migrate to wikidata from the full table. The code is at https://github.com/caffiendFrog/elife2019/tree/master/wikidatamigration
One of the pages edited: https://www.wikidata.org/wiki/Q44476657
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