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.

Insight into the Mechanism of the Acylation of Alcohols with Acid Anhydrides Catalyzed by Phosphoric Acid Derivatives

The Journal of Organic Chemistry(2021)10.1021/acs.joc.1c00102Source: DataRank Database

Insight into the Mechanism of the Acylation of Alcohols with Acid Anhydrides Catalyzed by Phosphoric Acid Derivatives is a research paper published in The Journal of Organic Chemistry (2021). On theSindex it has a DataRank of 0.651. It has been cited 17 times, with 16 citing works in its 1-hop citation network. Its calibrated FAIR score is 55/100.

N/A

0.651DataRank · unranked

0.651

17 citations · base score 2.9

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.

55FAIR score

F Findable

100

A Accessible

I Interoperable

R Reusable

Top 20% by FAIRdeterministic

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

DataRank Breakdown

Base Score 67%Citation Network 33%

Base Score Contribution

0.434

From this paper's citation signal

Citation Network Contribution

0.217

From 8 citing papers with measurable signal

Learn more about DataRank methodology →

Top 2 citers driving the network score

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

Highly Powerful and Practical Acylation of Alcohols with Acid Anhydride Catalyzed by Bi(OTf)<sub>3</sub>
The Journal of Organic Chemistry2001167 citationsDataRank 12.0
Bacterial protein acetylation: new discoveries unanswered questions
Current Genetics201680 citationsDataRank 3.0

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 67% comes from its base citations and 33% from the citation network (8 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 (5)

Shotaro Yasukochi,Tatsuhiro Sakamoto,Manabu HatanoORCID,Kazuaki IshiharaORCID,Hiroyuki Hayashi