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.

New Multinary Layered Chalcogenides with Octahedral and Tetrahedral Cation Coordination

Japanese Journal of Applied Physics(1993)10.7567/jjaps.32s3.781Source: DataRank Database

New Multinary Layered Chalcogenides with Octahedral and Tetrahedral Cation Coordination is a research paper published in Japanese Journal of Applied Physics (1993). On theSindex it has a DataRank of 0.985. It has been cited 8 times, with 7 citing works in its 1-hop citation network.

N/A

0.985DataRank · unranked

0.985

8 citations · base score 2.2

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Peculiarities of structure formation of layered chalcogenides with mixed tetrahedral and octahedral cation coodination are considered. The criterion for purposive search of new layered compounds was proposed. New layered compounds as Cu(Ag)Ga2.5In2.5S8, Mg0.5Ga2InS5, CuIn5S3Se5 and others were obtained and studied.

›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.

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DataRank Breakdown

Base Score 33%Citation Network 67%

Base Score Contribution

0.330

From this paper's citation signal

Citation Network Contribution

0.655

From 5 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 33% comes from its base citations and 67% from the citation network (5 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.

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Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank