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Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

Endosomal recycling regulation during cytokinesis

Communicative & Integrative Biology(2009)10.4161/cib.2.5.8931Source: DataRank Database

Endosomal recycling regulation during cytokinesis is a research paper published in Communicative & Integrative Biology (2009). On theSindex it has a DataRank of 1.6. It has been cited 32 times, with 32 citing works in its 1-hop citation network. Its calibrated FAIR score is 55/100.

N/A
1.6DataRank · unranked
1.6
32 citations · base score 3.5
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    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

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

        DataRank Breakdown

        Base Score 32%Citation Network 68%

        Base Score Contribution

        0.524

        From this paper's citation signal

        Citation Network Contribution

        1.1

        From 26 citing papers with measurable signal

        Learn more about DataRank methodology →

        Top 5 citers driving the network score

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

        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 32% comes from its base citations and 68% from the citation network (26 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 (2)

        Ahna R. Skop,Erkang Ai