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Augment's a PubMed literature search with citation data from NIH-OCC's iCite.

Project description

PubMed ID (PMID) Cite

Augment your PubMed literature search from the command-line by linking data downloaded from NIH's Open Citation Collection (NIH-OCC), which includes scientific influence, translation, and citation counts, with PubMed IDs (PMIDs), rather than clicking and clicking and clicking on Google Scholar Cited by N links.

Table of Contents

PubMed vs Google Scholar (GS)

GS vs PubMed

PubMed implements all five Boeker criteria [6]:

In late October 2013, Boeker et al. recommended that a scientific search interface contain five integrated search criteria. The 2013 Boeker guidance [6] greatly influenced the Gusenbauer study [4], which expanded the Boeker list from five search criteria to twenty-seven for their study of twenty-eight search tools.

The requirements for search interfaces are mandatory not only for structured scientific literature retrieval like systematic reviews, but also in any research that needs to provide a comprehensive literature review [6]. We add "Forward citation search" to the Boeker list to evaluate the extremely popular GS implementation of this feature through its ubiquitously featured "Cited by N" links against the PubMed implementation and compare PubMed and GS's support for the search tools below using the 2013 foundational Boeker advice [6].

Command-line users can immediately augment their PubMed search results using the pmidcite scripts and library, which download citation data from the National Institutes of Health Open Citation Collection (NIH-OCC) database using NIH's "iCite" Application Programming Interface (API). We have found PubMed plus NIH-OCC citation data combined using pmidcite is a "Better" experience than using Google Scholar if your research is in the health sciences and you are amenable to consider working from the command line.

What is in PubMed?

PubMed Contents

PubMed indexes about 30.5 million documents [1]:

PubMed is a search interface and toolset used to access databases like MEDLINE and PubMed Central (PMC) as well as additional content like books and articles published before the 1960s. Over 30.5 million article records are accessible through the PubMed interface. The databases, MEDLINE and PMC, are separate entities whose combined articles comprise 94% of all of the coverage indexed by PubMed ([1] S2). MEDLINE is a highly selective database started in the 1960s. PMC, started in 2000, is an open-access database for full-text papers that are free of cost to the researcher.

Take a quick tour of PubMed

Command Line Interface (CLI)

A Command-Line Interface (CLI) can be preferable to a Graphical User Interface (GUI) because: processing can be automated from a script; time-consuming mouse clicking is reduced; and more data can be seen at once on a text screen than in a browser, giving the researcher a better overall impression of the full set of information [1].

Linux and Mac users already work from the command line. Windows users can get that Linux-like command line feeling while still running native Windows programs by downloading Cygwin from [1].

1) Get citation counts, given PMIDs

Quickly get the number of citations for a research paper with PMID, 26032263:

$ icite 26032263 -H
TYP PMID     RP HAMCc   % SD YR   cit cli ref au[00](authors) title
TOP 26032263 R. .....  68 2 2015    16  0  10 au[04](N R Haddaway) Making literature reviews more reliable through application of lessons from systematic reviews.
  • The first line (TYP PMID ...) contains the column headers (-H).
  • The second line (TOP ...) is the citation data from NIH's iCite database.
  • The citation count, 16, is under the cit column header.

The group number, 2 (SD column) indicates that the paper has a good citation rate, specifically it is in the 68th percentile (% column) compared to its peers.

Column header key (-k)

$ icite -k

    TYP PubMedID RP HAMCc % SD YEAR x y z au[A](First Author) Title of paper

TYPe of relationship to the user-requested paper (TYP):
    TOP: A user-requested paper
    CIT: A paper that cited TOP
    CLI: A clinical paper that cited TOP
    REF: A paper referenced in the TOP paper's bibliography

NIH iCite details:

  PubMedID: PubMed ID (PMID)

     RP section:
         R: Is a research article
         P: iCite has calculated an initial Relative Citation Ratio (RCR) for new papers

     HAMCc section:
         H: Has MeSH terms in the human category
         A: Has MeSH terms in the animal category
         M: Has MeSH terms in the molecular/cellular biology category
         C: Is a clinical trial, study, or guideline
         c: Is cited by a clinical trial, study, or guideline

     NIH section, based on Relative Citation Ratio (RCR):
         %: NIH citation percentile rounded to an integer. -1 means "not determined" or TBD
        SD: NIH citation percentile group: 0=-3SD 1=-2SD 2=+/-1SD 3=+2SD 4=+3SD or i=TBD

     YEAR/citations/references section:
      YEAR: The year the article was published
         x: Total of all unique articles that have cited the paper, including clinical articles
         y: Number of unique clinical articles that have cited the paper
         z: Number of references
     au[A]: A is the number of authors

Citation group numbers [1]

The pmidcite citation rate group numbers, 0, 1, 2, 3, and 4 (SD column), are determined using the NIH Relative Citation Rate (RCR) [5] percentile. If the NIH has not yet determined a citation rate for new papers, the pmidcite group number is i.

cite group

2) Sort citation counts, given PMIDs

Sort the citations (CIT) of the paper with PMID 26032263 first by citation group (2 and i), then by year.

The citation group shown contains:

  • i New paper and not yet rated. The i variable will be set at a later date by the NIH
  • 2 These papers are performing well

Sort options:

  • -k6: sort starting with the 6th column containing citation group, then by all text to the right.
  • -r: reverse the sort so the newest papers are at the top
$ icite 26032263 -v | grep CIT | sort -k6 -r
CIT 32557171 .. H....  -1 i 2020     0  0  21 au[05](Jillian Knox) Usage, definition, and measurement of coexistence, tolerance and acceptance in wildlife conservation research in Africa.
CIT 32317639 R. HA...  -1 i 2020     0  0   8 au[09](Trevor J Krabbenhoft) FiCli, the Fish and Climate Change Database, informs climate adaptation and management for freshwater fishes.
CIT 30285277 R. .....  -1 i 2019     2  0  14 au[02](Neal R Haddaway) Predicting the time needed for environmental systematic reviews and systematic maps.
CIT 30055022 .. HA...  -1 i 2019     1  0  12 au[04](Hillary Smith) Hunting for common ground between wildlife governance and commons scholarship.
CIT 31598307 R. HA...  -1 i 2019     1  0  12 au[02](Igor Khorozyan) How long do anti-predator interventions remain effective? Patterns, thresholds and uncertainty.
CIT 31024221 R. .....  -1 i 2019     0  0   7 au[02](Micah G Bennett) MEASURING LOTIC ECOSYSTEM RESPONSES TO NUTRIENTS: A Mismatch that Limits the Synthesis and Application of Experimental Studies to Management.
CIT 29488217 .P .A...  76 2 2018     7  0  64 au[03](Nicole V Coggan) A global database and 'state of the field' review of research into ecosystem engineering by land animals.
CIT 29514874 .P .A...  47 2 2018     3  0  38 au[02](Kelly D Hannan) Aquatic acidification: a mechanism underpinning maintained oxygen transport and performance in fish experiencing elevated carbon dioxide conditions.
CIT 28642071 .. H....  75 2 2017    11  0  80 au[05](Ora Oudgenoeg-Paz) The link between motor and cognitive development in children born preterm and/or with low birth weight: A review of current evidence.
CIT 28061344 R. .....  70 2 2017     8  0  54 au[03](Maria Cristina Mangano) Monitoring of persistent organic pollutants in the polar regions: knowledge gaps & gluts through evidence mapping.
CIT 28042667 R. H....  53 2 2017     8  0  20 au[02](Martin J Westgate) The difficulties of systematic reviews.
CIT 29451529 .. H....  56 2 2016     9  0  20 au[01](Jennifer A Byrne) Improving the peer review of narrative literature reviews.
CIT 26984257 R. .....  46 2 2016     9  0   9 au[04](Neal R Haddaway) The benefits of systematic mapping to evidence-based environmental management.
CIT 27617203 .. .....  43 2 2016     5  0  40 au[02](Neal R Haddaway) On the benefits of systematic reviews for wildlife parasitology.

Other sort examples

We suggest starting with the -k6 sort option because in 2018 Fiorini et al. [7], the creaters of PubMed's "best match" relevance sort ordering in PubMed, found that the most important document features to feed into the PubMed sorting algorithm are publication year and past usage.

Using the -k6 argument to sort the citation group (usage group) does two things:

  • First, it highlights the newest or best performing papers by putting them at the beginning, while getting the lowest performing papers out of the mix by placing them at the end.
  • Second, it shows the newest papers first in each usage group, highlighting them profoundly.

We chose to highlight using usage group first, rather than NIH RCR percentile in the 5th column, seen with values -1, 76, etc. because only seeing the best performing papers first might bias the paper chosen for further examination to only the best performing papers regardless of publication year.

3) Query PubMed and download the citation data

Query PubMed and download the citation data from the script, src/bin/
NOTE: Copy to your project repo. Don't modify the pmidcite repo.

1. Add your query to your script

    queries = [
        # Output filename     PubMed query
        # -----------------  -----------------------------------
        ('killer_whale.txt', 'Orcinus Orca Type D'),

2. Run the script

$ src/bin/
     3 IDs FOR pubmed QUERY(Orcinus Orca Type D)
     3 WROTE: ./log/pmids/Orcinus_Orca_Type_D.txt
     3 WROTE: ./log/icite/Orcinus_Orca_Type_D.txt

3. Examine the citation and pubmed data, sorting by year (column 7; -k7)

$ grep TOP ./log/icite/Orcinus_Orca_Type_D.txt | sort -k7
TOP 20050301 R. .A...  70 2 2009    43  0  25 au[05](Andrew D Foote) Ecological, morphological and genetic divergence of sympatric North Atlantic killer whale populations.
TOP 22882545 .. .A...  63 2 2013    25  0  24 au[03](P J N de Bruyn) Killer whale ecotypes: is there a global model?
TOP 31461780 R. .A...  -1 i 2020     0  0   0 au[06](Robert L Pitman) Enigmatic megafauna: type D killer whale in the Southern Ocean.

4) Get citation data using PMIDs downloaded from PubMed

Note that the PubMed query using NIH E-Utils from the script will often be slightly different than the query run on the PubMed website. PubMed has been alerted.

Consequently, you may also want to view citation data on PMID PubMed query results downloaded from the PubMed website into a file like pmid-OrcinusOrc-set.txt:
Save->All results, Format=PMID

$ icite -i pmid-OrcinusOrc-set.txt
TOP 30123694 RP HA...  17 2 2018     1  0   6 au[07](Paul Tixier) Killer whale (<i>Orcinus orca</i>) interactions with blue-eye trevalla (<i>Hyperoglyphe antarctica</i>) longline fisheries.
TOP 31461780 R. .A...  -1 i 2020     0  0   0 au[06](Robert L Pitman) Enigmatic megafauna: type D killer whale in the Southern Ocean.
TOP 22882545 .. .A...  63 2 2013    25  0  24 au[03](P J N de Bruyn) Killer whale ecotypes: is there a global model?
TOP 20050301 R. .A...  70 2 2009    43  0  25 au[05](Andrew D Foote) Ecological, morphological and genetic divergence of sympatric North Atlantic killer whale populations.

5) Create ASCII plots

Create a scatter plot of publication year vs. citation count for a list of papers. This will be made more user friendly.

Columns 7 and 8 contain the year and the citation count.

$ grep TOP log/icite/Osbourn_Anne.txt | awk '{print $7 " " $8}' |
-------------------------------------------------------------------------------------------- 282
|                                                                1                         |
|                                                                                          |
|                                                                                          |
|                                                                                          |
|                                                                                          |
|                                                                                          |
|                                                                                          |
|                                                                                          |
|                              1                                                           |
|                                                                                          |
|               1                                                                          |
|                                                                                          |
|                                                                                          |
|                                                           1                              |
|          1                                                     1                         |
|1                                  1                                                      |
|                                                                                          |
|                                                      1                                   |
|                    1                   1                                                 |
|                                            1                   1                         |
|                                            1              1    1                         |
|     1                             1                                 1                    |
|                    1              1                  1    1                              |
|                              1             1              1                              |
|     1              1              1    1        2    2                                   |
|                                        1                            1    2               |
|                                                           1    2    1    1         1     |
|1    1                                  1   2    1    1              3    1    4          |
|               1         1    1         1   1    3    1    1    1              5          |
|          2         2                                           1    1    2    1    7    3|
-------------------------------------------------------------------------------------------- 0
2002                                                                                          2020


pip install pmidcite


Save your literature search in a GitHub repo.

1. Add a pmidcite init file

Add a .pmidciterc init file to a non-git managed directory, like home (~)

$ icite --generate-rcfile | tee ~/.pmidciterc
email =
apikey = long_hex_digit
tool = scripts
dir_icite_py = .
dir_pubmed_txt = .
dir_pmids = .
dir_icite = .
$ export PMIDCITECONF=~/.pmidciterc

You will want .pmidciterc to not be managed by GitHub because it will contain your personal email and your private NCBI API key.

2. Add directories

Add directories which match those in ~/.pmidciterc:

$ mkdir [GIT_REPO_PATH]/icite
$ mkdir [GIT_REPO_PATH]/log
$ mkdir [GIT_REPO_PATH]/log/pubmed
$ mkdir [GIT_REPO_PATH]/log/pmids
$ mkdir [GIT_REPO_PATH]/log/icite

3. NCBI E-Utils API key

If you want to download PubMed abstracts and PubMed search results using NCBI's E-Utils, get an NCBI API key using these instructions:

Set the apikey value in the config file: ~/.pmidciterc

How to Cite

If you use pmidcite in your research, please cite paper 1 (pmidcite) and paper 3 (citation data).
Please also consider reading and citing paper 2 (improving search for all):

  1. Commentary to Gusenbauer and Haddaway 2020: Evaluating Retrieval Qualities of PubMed and Google Scholar
    Klopfenstein DV and Dampier W
    2020 | Research Synthesis Methods | PMID: 33031632 | DOI: 10.1002/jrsm.1456 | pdfs

  2. The response to our commentary:
    What every Researcher should know about Searching – Clarified Concepts, Search Advice, and an Agenda to improve Finding in Academia
    Gusenbauer M and Haddaway N
    2020 | Research Synthesis Methods | PMID: 33031639 | DOI: 10.1002/jrsm.1457 | pdfs

  3. The data used by pmidcite: Scientific Influence, Translation, and Citation counts The NIH Open Citation Collection: A public access, broad coverage resource
    Hutchins BI ... Santangelo GM
    2019 | PLoS Biology | PMID: 31600197 | DOI: 10.1371/journal.pbio.3000385


Please consider reading and citing the paper [4] which inspired the creation of pmidcite and the authors' response to our paper [2]:

  1. Which Academic Search Systems are Suitable for Systematic Reviews or Meta-Analyses? Evaluating Retrieval Qualities of Google Scholar, PubMed and 26 other Resources
    Gusenbauer M and Haddaway N
    2019 | Research Synthesis Methods | PMID: 31614060 | DOI: 10.1002/jrsm.1378

Mentioned in this README are also these outstanding contributions:

  1. Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level
    Hutchins BI, Xin Yuan, Anderson JM, and Santangelo, George M.
    2016 | PLoS Biology | PMID: 27599104 | DOI: 10.1371/journal.pbio.1002541

  2. Google Scholar as replacement for systematic literature searches: good relative recall and precision are not enough
    Boeker M et al.
    2013 | BMC Medical Research Methodology | PMID: 24160679 | DOI: 10.1186/1471-2288-13-131

  3. Best Match: New relevance search for PubMed
    Fiorini N ... Lu Zhiyong
    2018 | PLoS Biology | PMID: 30153250 | DOI: 10.1371/journal.pbio.2005343

PDFs of our paper

Copyright (C) 2019-present, DV Klopfenstein. All rights reserved.

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