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.

Novel antibodies against follicular non-Hodgkin’s lymphoma

Best Practice & Research Clinical Haematology(2011)10.1016/j.beha.2011.03.002Source: DataRank Database

Novel antibodies against follicular non-Hodgkin’s lymphoma is a research paper published in Best Practice & Research Clinical Haematology (2011). On theSindex it has a DataRank of 1.2. It has been cited 25 times, with 24 citing works in its 1-hop citation network.

N/A

1.2DataRank · unranked

1.2

25 citations · base score 3.3

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.

Run a calibrated FAIR evaluation for this paper →

DataRank Breakdown

Base Score 40%Citation Network 60%

Base Score Contribution

0.489

From this paper's citation signal

Citation Network Contribution

0.724

From 18 citing papers with measurable signal

Learn more about DataRank methodology →

Top 3 citers driving the network score

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

Continuous cultures of fused cells secreting antibody of predefined specificity
Nature197517,123 citationsDataRank 1.5
Bevacizumab plus Irinotecan, Fluorouracil, and Leucovorin for Metastatic Colorectal Cancer
New England Journal of Medicine200410,954 citationsDataRank 1.4
CD20-Targeted Therapy: The Next Generation of Antibodies
Seminars in Hematology201092 citationsDataRank 4.6

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 40% comes from its base citations and 60% from the citation network (18 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