Kernel Metadata Declaration — on demand
ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.
✓ Meets every rule of the format
The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.
What the DOI identifies
STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING
10.46243/jst.2022.v7.i02.pp112-120 · JournalArticle — an article in a journal · Digital · Visual · Language · en
Published 2022-07-03
Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 7 · no. 2 · pp. 112–120
Principal agents
- Ravindra Nath Ravindra Nath (author → Author)
- Longman Publishers (publisher → Publisher)
Also in the record, outside the Kernel: the abstract, the licence, 4 links, 24 references. Source: Crossref (member 25296), registered 2024-02-16, last deposited 2026-09-17.
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name and the Handbook's (in grey), read off the record.
| DOI Name DOI name | 10.46243/jst.2022.v7.i02.pp112-120 |
| Referent Type referentType | Creation |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal |
| Referent Name(s) referentName(s) | STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING (PrincipalTitle, en) |
| Basic Metadata basicMetadata | author: Ravindra Nath Ravindra Nath publisher: Longman Publishers published: 2022-07-03 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 7 · no. 2 · pp. 112–120 language: en form: Digital · Visual · Language |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy |
| Created Date issueDate | 2024-02-16 |
| relatedIdentifiers | none needed — the descriptive metadata is in this record |
The record
{
"format": "smartscholars-doi-metadata/1.0",
"doi": "10.46243/jst.2022.v7.i02.pp112-120",
"referent": "Creation",
"type": "JournalArticle",
"structural_type": "Digital",
"modes": [
"Visual"
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"characters": [
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"titles": [
{
"value": "STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING",
"type": "PrincipalTitle",
"lang": "en"
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"identifiers": [
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},
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{
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"name": {
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"dates": {
"published": "2022-07-03",
"date_type": "PublicationDate",
"online": "2022-07-03"
},
"language": "en",
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"type": "Journal",
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"pages": {
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"last": "120"
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},
"links": [
{
"url": "https://www.jst.org.in/index.php/pub/article/view/395",
"return_type": "text/html",
"primary": true
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/395/352",
"purpose": "text-mining",
"return_type": "application/pdf"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/395/2234",
"purpose": "text-mining",
"return_type": "application/xml"
},
{
"url": "https://jst.org.in/admin/uploads/JST070201.pdf",
"purpose": "similarity-checking"
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],
"abstract": {
"value": "SARS-CoV-2, a novel coronavirus mostly known as COVID -19 has created a global pandemic. The world is now immobilized by this infectious RNA virus. This RNA virus has the ability to do the mutation in the human body. This study explores the mutation rate of the whole genomic sequence gathered from the patient's dataset of different countries. The collected dataset is processed to determine the nucleotide mutation and codon mutation separately. It has been found that a huge amount of Thymine (T) and Adenine (A) are mutated to other nucleotides for all regions, but codons are not frequently muta ting like nucleotides. Using this training and testing process, the nucleotide mutation rate of 400th patient in future time has been predicted. About 0.1% increment in mutation rate is found for mutating of nucleotides from T to C and G, C to G and G to T . While a decrement of 0.1% is seen for mutating of T to A, and A to C. It is found that this model can be used to predict day basis mutation rates if more patient data is available in updated time",
"lang": "en"
},
"license": {
"url": "https://creativecommons.org/licenses/by/4.0/",
"start": "2022-07-03",
"applies_to": "vor"
},
"references": [
{
"key": "ref1",
"unstructured": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293453"
},
{
"key": "ref2",
"unstructured": "kaggle.com/paultimothymooney/coronavirus-genome-sequence"
},
{
"key": "ref3",
"doi": "10.1038/s41564-020-0695-z",
"unstructured": "Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species severe acute respiratory syndromerelated coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nature Microbiology. 2020;5(4): 536‐544"
},
{
"key": "ref4",
"unstructured": "Laboratory testing of 2019 novel coronavirus (2019-nCoV) in suspected human cases: interim guidance, 17 January 2020"
},
{
"key": "ref5",
"doi": "10.1016/s0140-6736(20)30185-9",
"unstructured": "Wang C., Horby P.W., Hayden F.G., Gao G.F. A novel coronavirus outbreak of global health concern. Lancet North Am Ed. 2020;395(10223): 470–473"
},
{
"key": "ref6",
"unstructured": "Cucinotta D., Vanelli M. WHO declares COVID-19 a pandemic. Acta Bio-medica. 2020;91(1): 157–160"
},
{
"key": "ref7",
"doi": "10.1016/s0140-6736(20)30183-5",
"unstructured": "Huang C., Wang Y., Li X., Ren L., Zhao J., Hu Y., Cheng Z. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet North Am Ed. 2020;395(10223): 497–506"
},
{
"key": "ref8",
"doi": "10.1016/s0140-6736(20)30251-8",
"unstructured": "Lu R., Zhao X., Li J., Niu P., Yang B., Wu H., Bi Y. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet North Am Ed. 2020;395 (10224): 565–574"
},
{
"key": "ref9",
"doi": "10.1016/j.chom.2020.02.001",
"unstructured": "Wu A., Peng Y., Huang B., Ding X., Wang X., Niu P., Sheng J. Genome composition and divergence of the novel coronavirus (2019nCoV) originating in China. Cell Host Microbe"
},
{
"key": "ref10",
"doi": "10.1128/jvi.01394-09",
"unstructured": "Graham R.L., Baric R.S. Recombination, reservoirs, and the modular spike: mechanisms of coronavirus cross-species transmission. J Virol. 2010;84(7): 3134–3146"
},
{
"key": "ref11",
"doi": "10.1038/s41579-018-0118-9",
"unstructured": "Cui J., Li F., Shi Z.L. Origin and evolution of pathogenic coronaviruses. Nat Rev Microbiol. 2019;17(3): 181–192"
},
{
"key": "ref12",
"doi": "10.14218/jerp.2020.00005",
"unstructured": "Yang J. Inhibition of SARS-CoV-2 replication by acidizing and RNA lyase-modified carbon nanotubes combined with photodynamic thermal effect. J Explor Res Pharmacol. 2020: 1–6"
},
{
"key": "ref13",
"doi": "10.1007/978-1-4939-2438-7_1",
"unstructured": "Fehr A.R., Perlman S. Coronaviruses. Humana Press; New York, NY. Coronaviruses: an overview of their replication and pathogenesis. 2015: 1–23"
},
{
"key": "ref14",
"doi": "10.1186/s12967-020-02344-6",
"unstructured": "Pachetti M., Marini B., Benedetti F., Giudici F., Mauro E., Storici P., Zella D. Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med. 2020;18(1): 1–9"
},
{
"key": "ref15",
"unstructured": "Lodish H., Berk A., Zipursky S.L., Matsudaira P., Baltimore D., Darnell J. Mutations: types and causes. Mol Cell Biol. 2000; 4"
},
{
"key": "ref16",
"doi": "10.1128/jvi.00694-10",
"unstructured": "Sanjuán R., Nebot M.R., Chirico N., Mansky L.M., Belshaw R. Viral mutation rates. J Virol. 2010;84(19): 9733–9748"
},
{
"key": "ref17",
"doi": "10.1371/journal.ppat.0010011",
"unstructured": "Pfeiffer J.K., Kirkegaard K. Increased fidelity reduces poliovirus fitness and virulence under selective pressure in mice. PLoS Pathog. 2005;1(2)"
},
{
"key": "ref18",
"doi": "10.1038/nature04388",
"unstructured": "Vignuzzi M., Stone J.K., Arnold J.J., Cameron C.E., Andino R. Quasispecies diversity determines pathogenesis through cooperative interactions in a viral population. Nature. 2006;439(7074): 344–348"
},
{
"key": "ref19",
"doi": "10.1080/1040841x.2020.1739001",
"unstructured": "Biswas A., Bhattacharjee U., Chakrabarti A.K., Tewari D.N., Banu H., Dutta S. Emergence of Novel Coronavirus and COVID-19: whether to stay or die out? Crit Rev Microbiol. 2020; 1–12"
},
{
"key": "ref20",
"doi": "10.2196/preprints.19312",
"unstructured": "Das R., Ghate S.D. Investigating the likely association between genetic ancestry and COVID-19 manifestation. medRxiv"
},
{
"key": "ref21",
"doi": "10.1101/2020.04.26.062471",
"unstructured": "Bhowmik D., Pal S., Lahiri A., Talukdar A., Paul S. Emergence of multiple variants of SARS-CoV-2 with signature structural changes. bioRxiv"
},
{
"key": "ref22",
"doi": "10.1126/science.abb2507",
"unstructured": "Wrapp D., Wang N., Corbett K.S., Goldsmith J.A., Hsieh C.L., Abiona O., McLellan J.S. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science. 2020;367(6483): 1260–1263"
},
{
"key": "ref23",
"doi": "10.1016/j.nmni.2020.100682",
"unstructured": "Kumar G.V., Jeyanthi V., Ramakrishnan S. A short review on antibody therapy for COVID-19. New Microbes New Infect"
},
{
"key": "ref24",
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"unstructured": "Ojosnegros S., Beerenwinkel N. Models of RNA virus evolution and their roles in vaccine design. Immunome Res. 2010;6(S2): S5"
}
],
"record": {
"registrant": "Longman Publishers",
"registered": "2024-02-16",
"updated": "2026-09-17",
"issue_number": 1,
"source": "crossref-api",
"source_agency": "Crossref (member 25296)"
}
}The Kernel Metadata Declaration
DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation
<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
<kernelMetadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.doi.org/2010/DOISchema https://www.doi.org/doi_schemas/DOIMetadataKernel.xsd" xmlns="http://www.doi.org/2010/DOISchema">
<referentDoiName>10.46243/jst.2022.v7.i02.pp112-120</referentDoiName>
<primaryReferentType>Creation</primaryReferentType>
<registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
<issueDate>2026-10-04</issueDate>
<issueNumber>1</issueNumber>
<referentCreation>
<name primaryLanguage="en">
<value>STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING</value>
<type>PrincipalTitle</type>
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<identifier>
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<type>DOI</type>
</identifier>
<identifier>
<uri returnType="text/html">https://www.jst.org.in/index.php/pub/article/view/395</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/download/395/352</uri>
<type>URI</type>
</identifier>
<identifier>
<uri returnType="application/xml">https://www.jst.org.in/index.php/pub/article/download/395/2234</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://jst.org.in/admin/uploads/JST070201.pdf</uri>
<type>URI</type>
</identifier>
<structuralType>Digital</structuralType>
<mode>Visual</mode>
<character>Language</character>
<type>JournalArticle</type>
<principalAgent>
<name>
<value>Ravindra Nath Ravindra Nath</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Longman Publishers</value>
<type>PrincipalName</type>
</name>
<role>Publisher</role>
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<linkedCreation>
<name>
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<type>PrincipalTitle</type>
</name>
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<type>ISSN</type>
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<referentCreationRole>Part</referentCreationRole>
<referentCreationSequenceIdentifier>
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<value>112-120</value>
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<language>en</language>
<languageOfReferentContent>
<language>en</language>
<languageOfReferentContentType>Original</languageOfReferentContentType>
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