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
Machine Learning Based Brain Tumor Detection
10.46243/jst.2021.v6.i04.pp131-136 · JournalArticle — an article in a journal · Digital · Visual · Language · en
Published 2021-08-16
Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 06 · no. 01 · pp. 131–136
Principal agents
- Rajshri Shelke (author → Author)
- Tanmay Sutar (author → Author)
- Suraj Gayakwad (author → Author)
- Longman Publishers (publisher → Publisher)
Also in the record, outside the Kernel: the abstract, the licence, 4 links, 4 references. Source: Crossref (member 25296), registered 2026-09-11, last deposited 2026-09-20.
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.2021.v6.i04.pp131-136 |
| Referent Type referentType | Creation |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal |
| Referent Name(s) referentName(s) | Machine Learning Based Brain Tumor Detection (PrincipalTitle, en) |
| Basic Metadata basicMetadata | author: Rajshri Shelke author: Tanmay Sutar author: Suraj Gayakwad publisher: Longman Publishers published: 2021-08-16 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 06 · no. 01 · pp. 131–136 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 | 2026-09-11 |
| relatedIdentifiers | none needed — the descriptive metadata is in this record |
The record
{
"format": "smartscholars-doi-metadata/1.0",
"doi": "10.46243/jst.2021.v6.i04.pp131-136",
"referent": "Creation",
"type": "JournalArticle",
"structural_type": "Digital",
"modes": [
"Visual"
],
"characters": [
"Language"
],
"titles": [
{
"value": "Machine Learning Based Brain Tumor Detection",
"type": "PrincipalTitle",
"lang": "en"
}
],
"identifiers": [
{
"type": "DOI",
"value": "10.46243/jst.2021.v6.i04.pp131-136"
}
],
"agents": [
{
"role": "author",
"name": {
"given": "Rajshri",
"family": "Shelke"
},
"sequence": "first"
},
{
"role": "author",
"name": {
"given": "Tanmay",
"family": "Sutar"
},
"sequence": "additional"
},
{
"role": "author",
"name": {
"given": "Suraj",
"family": "Gayakwad"
},
"sequence": "additional"
},
{
"role": "publisher",
"name": {
"org": "Longman Publishers"
}
}
],
"dates": {
"published": "2021-08-16",
"date_type": "PublicationDate",
"online": "2021-08-16"
},
"language": "en",
"container": {
"type": "Journal",
"titles": [
{
"value": "Journal of Science & Technology",
"type": "PrincipalTitle"
}
],
"identifiers": [
{
"type": "ISSN",
"value": "2456-5660",
"medium": "electronic"
}
],
"volume": "06",
"issue": "01",
"pages": {
"first": "131",
"last": "136"
}
},
"links": [
{
"url": "https://www.jst.org.in/index.php/pub/article/view/734",
"return_type": "text/html",
"primary": true
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/734/660",
"purpose": "text-mining",
"return_type": "application/pdf"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/734/2861",
"purpose": "text-mining",
"return_type": "application/xml"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/view/734/660",
"purpose": "similarity-checking"
}
],
"abstract": {
"value": "The brain tumors, are the most common and aggressive disease and it is challenging task to detect brain tumor in early stages of life, it leads to a very short life expectancy in their highest grade. Thus, treatment planning will be a key stage to improve the quality of life of patients. To evaluate the tumor in a brain used various image techniques such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and ultrasound image etc. Mostly, in this work MRI images are used to diagnose tumor in the brain. The huge amount of data generated by MRI scan that helps to classify tumor vs non-tumor in a particular time. But it having some limitation (i.e.) accurate quantitative measurements will be provided for limited number of images. To prevent death rate of human trusted and automatic classification scheme are essential. The automatic brain tumor classification will be very challenging task in large spatial and structural variability of surrounding region of brain tumor. In this work, automatic brain tumor detection will be proposed by using Convolutional Neural Networks (CNN) classification. The deeper architecture design will be performed by using small kernels. The weight of the neuron will be given as small.",
"lang": "en"
},
"license": {
"url": "https://creativecommons.org/licenses/by/4.0",
"start": "2021-08-16",
"applies_to": "vor"
},
"references": [
{
"key": "ref1",
"doi": "10.1016/j.cmpb.2019.05.015",
"unstructured": "Javaria Amin et al,” Brain tumor detection using statistical and machine learning method”, Journal, vol 177, Aug 2019"
},
{
"key": "ref2",
"doi": "10.1145/2222444.2222467",
"unstructured": "Ghaith Husani, Omar Darwish, et al,” Machine learning approach for Brain tumor detection”..Kimmi Verna et al,” Image processing techniques for the enhancement of brain tumor patterns ”,international"
},
{
"key": "ref3",
"unstructured": "journal of advanced research in electrical, electronics and instrumentation engineering, Apr 2013"
},
{
"key": "ref4",
"unstructured": "Harshini Badisa et al. “CNN based brain tumor detection ”,international journal of engineering and advanced technology, Apr 2019. [5].J Seetha et al,” Brain tumor classification using CNN ”,Biomedical and pharmacology journal,Sep 2018 [6].Dena Nadir George. M et al. “Brain tumor detection using shape features and machine learning algorithm”, international journal of scientific and engineering research, Dec 2015"
}
],
"record": {
"registrant": "Longman Publishers",
"registered": "2026-09-11",
"updated": "2026-09-20",
"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.2021.v6.i04.pp131-136</referentDoiName>
<primaryReferentType>Creation</primaryReferentType>
<registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
<issueDate>2026-10-04</issueDate>
<issueNumber>1</issueNumber>
<referentCreation>
<name primaryLanguage="en">
<value>Machine Learning Based Brain Tumor Detection</value>
<type>PrincipalTitle</type>
</name>
<identifier>
<nonUriValue>10.46243/jst.2021.v6.i04.pp131-136</nonUriValue>
<uri returnType="text/html" doesContentNegotiation="true">https://doi.org/10.46243/jst.2021.v6.i04.pp131-136</uri>
<type>DOI</type>
</identifier>
<identifier>
<uri returnType="text/html">https://www.jst.org.in/index.php/pub/article/view/734</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/download/734/660</uri>
<type>URI</type>
</identifier>
<identifier>
<uri returnType="application/xml">https://www.jst.org.in/index.php/pub/article/download/734/2861</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/view/734/660</uri>
<type>URI</type>
</identifier>
<structuralType>Digital</structuralType>
<mode>Visual</mode>
<character>Language</character>
<type>JournalArticle</type>
<principalAgent>
<name>
<value>Rajshri Shelke</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Tanmay Sutar</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Suraj Gayakwad</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Longman Publishers</value>
<type>PrincipalName</type>
</name>
<role>Publisher</role>
</principalAgent>
<linkedCreation>
<name>
<value>Journal of Science & Technology</value>
<type>PrincipalTitle</type>
</name>
<identifier>
<nonUriValue>2456-5660</nonUriValue>
<type>ISSN</type>
</identifier>
<referentCreationRole>Part</referentCreationRole>
<referentCreationSequenceIdentifier>
<value>06</value>
<type>VolumeNumber</type>
</referentCreationSequenceIdentifier>
<referentCreationSequenceIdentifier>
<value>01</value>
<type>IssueNumber</type>
</referentCreationSequenceIdentifier>
<referentCreationSequenceIdentifier>
<value>131-136</value>
<type>PageNumber</type>
</referentCreationSequenceIdentifier>
</linkedCreation>
<language>en</language>
<languageOfReferentContent>
<language>en</language>
<languageOfReferentContentType>Original</languageOfReferentContentType>
</languageOfReferentContent>
<creationDate>
<date>2021-08-16</date>
<creationDateType>PublicationDate</creationDateType>
</creationDate>
</referentCreation>
</kernelMetadata>
