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.

Covariance adjustment of survival curves based on Cox<sup>′</sup>s proportional hazards regression model

Bioinformatics(1992)10.1093/bioinformatics/8.1.23Source: DataRank Database

Covariance adjustment of survival curves based on Cox<sup>′</sup>s proportional hazards regression model is a research paper published in Bioinformatics (1992). On theSindex it has a DataRank of 3.5. It has been cited 23 times, with 22 citing works in its 1-hop citation network. Its calibrated FAIR score is 43/100.

N/A

3.5DataRank · unranked

3.5

23 citations · base score 3.2

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.

43FAIR score

F Findable

100

A Accessible

I Interoperable

R Reusable

Top 79% by FAIRdeterministic

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

DataRank Breakdown

Base Score 14%Citation Network 86%

Base Score Contribution

0.477

From this paper's citation signal

Citation Network Contribution

3.1

From 21 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 14% comes from its base citations and 86% from the citation network (21 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