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Badomics words and the power and peril of the ome-meme

GigaScience(2012)10.1186/2047-217x-1-6Source: DataRank Database

Badomics words and the power and peril of the ome-meme is a research paper published in GigaScience (2012). On theSindex it has a DataRank of 1.8. It has been cited 15 times, with 15 citing works in its 1-hop citation network. Its calibrated FAIR score is 55/100.

N/A
1.8DataRank · unranked
1.8
Open Access15 citations · base score 2.8
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Languages and cultures, like organisms, are constantly evolving. Words, like genes, can come and go-spreading around or going extinct. Here I discuss the spread of one small subset of words that are meant to convey "comprehensiveness" in some way: the "omes" and other words derived from "genome" or "genomics." I focus on a bad aspect of this spread the use of what I refer to as "badomics" words. I discuss why these should be considered bad and how to distinguish badomics words from good ones.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (1/2)
  • Open Access
Interoperable (0/2)
    Reusable (0/3)

      FAIR checklist signals are shown for context only and do not affect DataRank scoring.

      55FAIR score
      F Findable
      100
      A Accessible
      70
      I Interoperable
      0
      R Reusable
      50
      Top 20% by FAIRdeterministic✓ full text read

      Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →

      DataRank Breakdown

      Base Score 23%Citation Network 77%

      Base Score Contribution

      0.416

      From this paper's citation signal

      Citation Network Contribution

      1.4

      From 13 citing papers with measurable signal

      Learn more about DataRank methodology →

      Top 1 citer driving the network score

      Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

      1. Large and linked in scientific publishing
        GigaScience2012203 citationsDataRank 11.4Top 19%
      Why this DataRank?

      DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 23% comes from its base citations and 77% from the citation network (13 citing papers contributed measurable signal).

      Base score B(p)
      log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
      Network N(p)
      Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
      Damping factor d = 0.85
      DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
      Self-citations excluded
      Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

      Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

      Read the full methodology →

      Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

      Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

      Authors (1)

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