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.

Effects of phosphite on the in vitro growth of Verticillium nonalfalfae and Verticillium dahliae and on their in vivo ability to infect potato plants

European Journal of Plant Pathology(2019)10.1007/s10658-019-01859-zSource: DataRank Database

Effects of phosphite on the in vitro growth of Verticillium nonalfalfae and Verticillium dahliae and on their in vivo ability to infect potato plants is a research paper published in European Journal of Plant Pathology (2019). On theSindex it has a DataRank of 0.401. It has been cited 8 times, with 4 citing works in its 1-hop citation network. Its calibrated FAIR score is 49/100.

N/A

0.401DataRank · unranked

0.401

8 citations · base score 2.2

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.

49FAIR score

F Findable

100

A Accessible

I Interoperable

R Reusable

Top 55% by FAIRdeterministic

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

DataRank Breakdown

Base Score 82%Citation Network 18%

Base Score Contribution

0.330

From this paper's citation signal

Citation Network Contribution

0.0713

From 4 citing papers with measurable signal

Learn more about DataRank methodology →

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 82% comes from its base citations and 18% from the citation network (4 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(C_q) ÷ max(outdegree_q, 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 →

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