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.

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

Journal of Chemical Information and Computer Sciences(1988)10.1021/ci00057a005Source: DataRank Database

SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules is a research paper published in Journal of Chemical Information and Computer Sciences (1988). On theSindex it has a DataRank of 1.3. It has been cited 7,478 times.

N/A

1.3DataRank · unranked

1.3

7478 citations · base score 8.9

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTSMILES, a chemical language and information system. 1. Introduction to methodology and encoding rulesDavid WeiningerCite this: J. Chem. Inf. Comput. Sci. 1988, 28, 1, 31–36Publication Date (Print):February 1, 1988Publication History Published online1 May 2002Published inissue 1 February 1988https://pubs.acs.org/doi/10.1021/ci00057a005https://doi.org/10.1021/ci00057a005research-articleACS PublicationsRequest reuse permissionsArticle Views12790Altmetric-Citations4077LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access options Get e-Alerts

›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.

Run a calibrated FAIR evaluation for this paper →

DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

1.3

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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 100% comes from its base citations and 0% from the citation network.

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 →