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.

Preprint Servers’ Policies, Submission Requirements, and Transparency in Reporting and Research Integrity Recommendations

JAMA(2020)10.1001/jama.2020.17195Source: DataRank Database

Preprint Servers’ Policies, Submission Requirements, and Transparency in Reporting and Research Integrity Recommendations is a research paper published in JAMA (2020). On theSindex it has a DataRank of 4.4. It has been cited 78 times, with 70 citing works in its 1-hop citation network.

N/A

4.4DataRank · unranked

4.4

Open Access78 citations · base score 4.4

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

This study describes the policies, submission requirements, and transparency in reporting and research integrity recommendations of academic preprint servers.

›Data sources & pipeline

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Pending

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

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 15%Citation Network 85%

Base Score Contribution

0.655

From this paper's citation signal

Citation Network Contribution

3.8

From 44 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 present and future of peer review: Ideas, interventions, and evidence
Proceedings of the National Academy of Sciences202546 citationsDataRank 0.578
Statistical Guidance to Authors at Top-Ranked Journals across Scientific Disciplines
The American Statistician202213 citationsDataRank 0.396
TIER2: enhancing Trust, Integrity and Efficiency in Research through next-level Reproducibility
Research Ideas and Outcomes20221 citationsDataRank 0.104

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 15% comes from its base citations and 85% from the citation network (44 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