🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge
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.

The medial entorhinal cortex is necessary for temporal organization of hippocampal neuronal activity

Nature Neuroscience(2015)10.1038/nn.4056Source: DataRank Database
N/A
6.0DataRank · unranked
6.0
188 citations · base score 5.2
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.

        DataRank Breakdown

        Base Score 13%Citation Network 87%

        Base Score Contribution

        0.786

        From this paper's citation signal

        Citation Network Contribution

        5.2

        From 142 citing papers with measurable signal

        Learn more about DataRank methodology →

        Top citers

        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 13% comes from its base citations and 87% from the citation network (142 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 →

        Authors (9)

        Christopher C Cannova,Brittney L Boublil,Jena B Hales,Emily A Mankin,Mark P Brandon

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