{"id":"https://openalex.org/W7225411880","doi":"https://doi.org/10.46687/jsar.v31i1.501","title":"CONCEPTUAL MODEL FOR GENDER PREDICTION BASED ON USER INPUT","display_name":"CONCEPTUAL MODEL FOR GENDER PREDICTION BASED ON USER INPUT","publication_year":2026,"publication_date":"2026-11-06","ids":{"openalex":"https://openalex.org/W7225411880","doi":"https://doi.org/10.46687/jsar.v31i1.501"},"language":"en","primary_location":{"id":"doi:10.46687/jsar.v31i1.501","doi":"https://doi.org/10.46687/jsar.v31i1.501","is_oa":true,"landing_page_url":"https://doi.org/10.46687/jsar.v31i1.501","pdf_url":"https://jsar.ftn.shu.bg/index.php/jsar/article/download/501/498/1994","source":{"id":"https://openalex.org/S4387287558","display_name":"Journal Scientific and Applied Research","issn_l":"1314-6289","issn":["1314-6289","2815-4622"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal Scientific and Applied Research","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://jsar.ftn.shu.bg/index.php/jsar/article/download/501/498/1994","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041873952","display_name":"Valentin Atanasov","orcid":"https://orcid.org/0000-0002-0179-6042","observed_orcids":["https://orcid.org/0000-0002-0179-6042"]},"institutions":[{"id":"https://openalex.org/I39995536","display_name":"Shumen University","ror":"https://ror.org/03yht3k11","country_code":"BG","type":"education","lineage":["https://openalex.org/I39995536"]}],"countries":["BG"],"is_corresponding":true,"raw_author_name":"Valentin Atanasov","raw_affiliation_strings":["Department of Communication and Computer Engineering and Security Technologies, Faculty of Technical Sciences, Konstantin Preslavsky University of Shumen, Shumen 9712, 115 Universitetska St., e-mail: v.atanasov@shu.bg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Communication and Computer Engineering and Security Technologies, Faculty of Technical Sciences, Konstantin Preslavsky University of Shumen, Shumen 9712, 115 Universitetska St., e-mail: v.atanasov@shu.bg","institution_ids":["https://openalex.org/I39995536"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5041873952"],"corresponding_institution_ids":["https://openalex.org/I39995536"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"1","first_page":"59","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.6582000255584717,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.6582000255584717,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":0.17790000140666962,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.04520000144839287,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gender-estimation","display_name":"gender prediction","score":0.9959999918937683},{"id":"https://openalex.org/keywords/conceptual-model","display_name":"conceptual model","score":0.7329999804496765},{"id":"https://openalex.org/keywords/user-input","display_name":"user input","score":0.9710000157356262},{"id":"https://openalex.org/keywords/machine-learning-classification","display_name":"machine learning classification","score":0.7649999856948853},{"id":"https://openalex.org/keywords/bioindicators","display_name":"bioindicators","score":0.7239999771118164},{"id":"https://openalex.org/keywords/language","display_name":"language","score":0.6660000085830688},{"id":"https://openalex.org/keywords/sample-size","display_name":"sample size","score":0.824999988079071},{"id":"https://openalex.org/keywords/gender-classification","display_name":"gender classification","score":0.5149999856948853}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6625999808311462},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5239999890327454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5171999931335449},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C13606891","wikidata":"https://www.wikidata.org/wiki/Q2623243","display_name":"Conceptual model","level":2,"score":0.48660001158714294},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.484499990940094},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47620001435279846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47510001063346863},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4569000005722046},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.2784999907016754}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.46687/jsar.v31i1.501","doi":"https://doi.org/10.46687/jsar.v31i1.501","is_oa":true,"landing_page_url":"https://doi.org/10.46687/jsar.v31i1.501","pdf_url":"https://jsar.ftn.shu.bg/index.php/jsar/article/download/501/498/1994","source":{"id":"https://openalex.org/S4387287558","display_name":"Journal Scientific and Applied Research","issn_l":"1314-6289","issn":["1314-6289","2815-4622"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal Scientific and Applied Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.46687/jsar.v31i1.501","doi":"https://doi.org/10.46687/jsar.v31i1.501","is_oa":true,"landing_page_url":"https://doi.org/10.46687/jsar.v31i1.501","pdf_url":"https://jsar.ftn.shu.bg/index.php/jsar/article/download/501/498/1994","source":{"id":"https://openalex.org/S4387287558","display_name":"Journal Scientific and Applied Research","issn_l":"1314-6289","issn":["1314-6289","2815-4622"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal Scientific and Applied Research","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6025999784469604,"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225411880.pdf","grobid_xml":"https://content.openalex.org/works/W7225411880.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W351978010","https://openalex.org/W2157825442","https://openalex.org/W2790688901","https://openalex.org/W3002867195","https://openalex.org/W4416668265","https://openalex.org/W7169171161"],"related_works":["https://openalex.org/W2775624196","https://openalex.org/W2784268700","https://openalex.org/W7217444898","https://openalex.org/W4416927447","https://openalex.org/W2274175597","https://openalex.org/W7067613093","https://openalex.org/W6922311469","https://openalex.org/W3162890489","https://openalex.org/W4380148253","https://openalex.org/W4406322394"],"abstract_inverted_index":{"The":[0,20,44],"present":[1],"study":[2],"examines":[3],"an":[4],"approach":[5],"to":[6],"the":[7,24,37,56,59],"synthesis":[8],"of":[9,23,39,52,58,75,82],"a":[10,40,50,76,80],"conceptual":[11],"model":[12,25],"for":[13],"gender":[14,78],"prediction":[15],"based":[16],"on":[17],"user":[18],"input.":[19],"predictive":[21,45],"capability":[22],"is":[26,47,79],"grounded":[27],"in":[28,36],"statistical":[29],"differences":[30],"observed":[31],"within":[32],"specific":[33],"datasets":[34],"and":[35,65],"applicability":[38],"machine-learning":[41],"classification":[42,74],"model.":[43],"analysis":[46],"governed":[48],"by":[49],"set":[51],"parameters,":[53],"including":[54],"language,":[55],"specifications":[57],"peripheral":[60],"input":[61],"device,":[62],"sample":[63],"size,":[64],"biological":[66],"indicators.":[67,85],"It":[68],"should":[69],"be":[70],"noted":[71],"that":[72],"reliable":[73],"user's":[77],"function":[81],"predefined":[83],"key":[84]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-07T00:00:00"}