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.

BoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples

Analytical Chemistry(2021)10.1021/acs.analchem.0c04293Source: DataRank Database

BoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples is a research paper published in Analytical Chemistry (2021). On theSindex it has a DataRank of 1.4. It has been cited 41 times, with 32 citing works in its 1-hop citation network. Its calibrated FAIR score is 61/100.

N/A

1.4DataRank · unranked

1.4

41 citations · base score 3.7

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.

61FAIR score

F Findable

100

A Accessible

I Interoperable

R Reusable

Top 7% by FAIRdeterministic

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

DataRank Breakdown

Base Score 41%Citation Network 59%

Base Score Contribution

0.561

From this paper's citation signal

Citation Network Contribution

0.804

From 29 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.

The Perseus computational platform for comprehensive analysis of (prote)omics data
Nature Methods20168,788 citationsDataRank 12.5Top 16%
The PRIDE database and related tools and resources in 2019: improving support for quantification data
Nucleic Acids Research20187,380 citationsDataRank 15.0Top 13%
Global quantification of mammalian gene expression control
Nature20116,828 citationsDataRank 1.3

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 41% comes from its base citations and 59% from the citation network (29 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 →

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 (4)

Wenxue Li,Yi DiORCID,Yansheng LiuORCID,Barbora SalovskaORCID