{"id":"https://openalex.org/W7202349583","doi":"https://doi.org/10.1109/tcss.2026.3724012","title":"A Cascaded Unsupervised\u2013Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","display_name":"A Cascaded Unsupervised\u2013Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7202349583","doi":"https://doi.org/10.1109/tcss.2026.3724012"},"language":"en","primary_location":{"id":"doi:10.1109/tcss.2026.3724012","doi":"https://doi.org/10.1109/tcss.2026.3724012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2026.3724012","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-c","cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.12269","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5147079993","display_name":"Bryan Torres","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I69094615","display_name":"Universidad San Francisco de Quito","ror":"https://ror.org/01r2c3v86","country_code":"EC","type":"education","lineage":["https://openalex.org/I69094615"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Bryan Torres","raw_affiliation_strings":["Universidad San Francisco de Quito (USFQ)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad San Francisco de Quito (USFQ)","institution_ids":["https://openalex.org/I69094615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020124958","display_name":"Daniel Riofr\u00edo","orcid":"https://orcid.org/0000-0001-9815-2659","observed_orcids":["https://orcid.org/0000-0001-9815-2659"]},"institutions":[{"id":"https://openalex.org/I69094615","display_name":"Universidad San Francisco de Quito","ror":"https://ror.org/01r2c3v86","country_code":"EC","type":"education","lineage":["https://openalex.org/I69094615"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Daniel Riofrio","raw_affiliation_strings":["Universidad San Francisco de Quito (USFQ)"],"raw_orcid":"https://orcid.org/0000-0001-9815-2659","affiliations":[{"raw_affiliation_string":"Universidad San Francisco de Quito (USFQ)","institution_ids":["https://openalex.org/I69094615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037217242","display_name":"Jos\u00e9 David Vega-S\u00e1nchez","orcid":"https://orcid.org/0000-0002-3305-1109","observed_orcids":["https://orcid.org/0000-0002-3305-1109"]},"institutions":[{"id":"https://openalex.org/I69094615","display_name":"Universidad San Francisco de Quito","ror":"https://ror.org/01r2c3v86","country_code":"EC","type":"education","lineage":["https://openalex.org/I69094615"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Jose Vega-Sanchez","raw_affiliation_strings":["Universidad San Francisco de Quito (USFQ)"],"raw_orcid":"https://orcid.org/0000-0002-3305-1109","affiliations":[{"raw_affiliation_string":"Universidad San Francisco de Quito (USFQ)","institution_ids":["https://openalex.org/I69094615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007382966","display_name":"Nathaly Orozco Garz\u00f3n","orcid":"https://orcid.org/0000-0002-5232-7529","observed_orcids":["https://orcid.org/0000-0002-5232-7529"]},"institutions":[{"id":"https://openalex.org/I4210100770","display_name":"University of the Americas","ror":"https://ror.org/0166e9x11","country_code":"CL","type":"education","lineage":["https://openalex.org/I4210100770"]},{"id":"https://openalex.org/I4210102282","display_name":"Universidad de Las Am\u00e9ricas","ror":"https://ror.org/0198j4566","country_code":"EC","type":"education","lineage":["https://openalex.org/I4210102282"]},{"id":"https://openalex.org/I4210120382","display_name":"Universidad de las Am\u00e9ricas","ror":"https://ror.org/02j003371","country_code":"MX","type":"education","lineage":["https://openalex.org/I4210120382"]}],"countries":["CL","EC","MX"],"is_corresponding":false,"raw_author_name":"Nathaly Orozco Garzon","raw_affiliation_strings":["Universidad de Las Am\u00e9ricas (UDLA)"],"raw_orcid":"https://orcid.org/0000-0002-5232-7529","affiliations":[{"raw_affiliation_string":"Universidad de Las Am\u00e9ricas (UDLA)","institution_ids":["https://openalex.org/I4210100770","https://openalex.org/I4210102282","https://openalex.org/I4210120382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074622722","display_name":"Carla Parra","orcid":"https://orcid.org/0000-0002-7974-471X","observed_orcids":["https://orcid.org/0000-0002-7974-471X"]},"institutions":[{"id":"https://openalex.org/I70764802","display_name":"National Polytechnic School","ror":"https://ror.org/01gb99w41","country_code":"EC","type":"education","lineage":["https://openalex.org/I70764802"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Carla Parra","raw_affiliation_strings":["Escuela Polit\u00e9cnica Nacional"],"raw_orcid":"https://orcid.org/0000-0002-7974-471X","affiliations":[{"raw_affiliation_string":"Escuela Polit\u00e9cnica Nacional","institution_ids":["https://openalex.org/I70764802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002311406","display_name":"Karen Rosero","orcid":"https://orcid.org/0000-0002-8118-4213","observed_orcids":["https://orcid.org/0000-0002-8118-4213"]},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karen Rosero","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":"https://orcid.org/0000-0002-8118-4213","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121288284","display_name":"Felipe Grijalva","orcid":"https://orcid.org/0000-0001-6162-3429","observed_orcids":["https://orcid.org/0000-0001-6162-3429"]},"institutions":[{"id":"https://openalex.org/I69094615","display_name":"Universidad San Francisco de Quito","ror":"https://ror.org/01r2c3v86","country_code":"EC","type":"education","lineage":["https://openalex.org/I69094615"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Felipe Grijalva","raw_affiliation_strings":["Universidad San Francisco de Quito (USFQ)"],"raw_orcid":"https://orcid.org/0000-0001-6162-3429","affiliations":[{"raw_affiliation_string":"Universidad San Francisco de Quito (USFQ)","institution_ids":["https://openalex.org/I69094615"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"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":null,"issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.46880000829696655,"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/T10028","display_name":"Topic Modeling","score":0.46880000829696655,"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/T12779","display_name":"Public Procurement and Policy","score":0.25200000405311584,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.10029999911785126,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/public-procurement","display_name":"public procurement","score":0.9470000267028809},{"id":"https://openalex.org/keywords/procurement-irregularities","display_name":"procurement irregularities","score":0.8640000224113464},{"id":"https://openalex.org/keywords/stakeholder-feedback","display_name":"stakeholder feedback","score":0.6690000295639038},{"id":"https://openalex.org/keywords/unsupervised-clustering","display_name":"unsupervised clustering","score":0.781000018119812},{"id":"https://openalex.org/keywords/gaussian-mixture-model","display_name":"Gaussian mixture model","score":0.9599999785423279},{"id":"https://openalex.org/keywords/word2vec-embeddings","display_name":"Word2Vec embeddings","score":0.8009999990463257},{"id":"https://openalex.org/keywords/roberta","display_name":"RoBERTa","score":0.7369999885559082},{"id":"https://openalex.org/keywords/llama","display_name":"llamas","score":0.8700000047683716},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.718999981880188},{"id":"https://openalex.org/keywords/procurement-transparency","display_name":"procurement transparency","score":0.5350000262260437}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.766700029373169},{"id":"https://openalex.org/C201650216","wikidata":"https://www.wikidata.org/wiki/Q829492","display_name":"Procurement","level":2,"score":0.6635000109672546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6126000285148621},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.551800012588501},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4950999915599823},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4632999897003174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45500001311302185},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42809998989105225},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.32910001277923584},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3068000078201294},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C2777299493","wikidata":"https://www.wikidata.org/wiki/Q151480","display_name":"Sphinx","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25380000472068787}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tcss.2026.3724012","doi":"https://doi.org/10.1109/tcss.2026.3724012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcss.2026.3724012","pdf_url":null,"source":{"id":"https://openalex.org/S2490693980","display_name":"IEEE Transactions on Computational Social Systems","issn_l":"2329-924X","issn":["2329-924X","2373-7476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-c","cwts-core","dongbi-d","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Social Systems","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2608.12269","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.12269","pdf_url":"https://arxiv.org/pdf/2608.12269","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.12269","doi":"https://doi.org/10.48550/arxiv.2608.12269","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.12269","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.12269","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.12269","pdf_url":"https://arxiv.org/pdf/2608.12269","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","score":0.9258999824523926,"id":"https://metadata.un.org/sdg/16"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G2096730396","display_name":null,"funder_award_id":"41990","funder_id":"https://openalex.org/F4320326549","funder_display_name":"Universidad San Francisco de Quito"},{"id":"https://openalex.org/G666413011","display_name":null,"funder_award_id":"41989","funder_id":"https://openalex.org/F4320326549","funder_display_name":"Universidad San Francisco de Quito"}],"funders":[{"id":"https://openalex.org/F4320326549","display_name":"Universidad San Francisco de Quito","ror":"https://ror.org/01r2c3v86"},{"id":"https://openalex.org/F4320326821","display_name":"Deutsche Gesellschaft f\u00fcr Internationale Zusammenarbeit","ror":"https://ror.org/00q08t645"},{"id":"https://openalex.org/F4320338362","display_name":"FP7 International Cooperation","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202349583.pdf","grobid_xml":"https://content.openalex.org/works/W7202349583.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2965373594","https://openalex.org/W4225631575","https://openalex.org/W4308242686","https://openalex.org/W4375869806","https://openalex.org/W4390528756","https://openalex.org/W4394708953","https://openalex.org/W4405311063"],"related_works":["https://openalex.org/W4327518009","https://openalex.org/W4405175775","https://openalex.org/W7140172026","https://openalex.org/W7167079153","https://openalex.org/W7203605708","https://openalex.org/W7117248288","https://openalex.org/W4415598381","https://openalex.org/W6949995535","https://openalex.org/W4210692212","https://openalex.org/W3039577790"],"abstract_inverted_index":{"Public":[0,55],"procurement":[1,97,175],"involves":[2],"the":[3,66,134],"allocation":[4],"of":[5,136],"substantial":[6],"financial":[7],"resources;":[8],"therefore,":[9],"continuous":[10],"oversight":[11],"through":[12],"audits,":[13],"controls,":[14],"and":[15,23,79,93,106,142,150,170],"monitoring":[16],"mechanisms":[17],"is":[18,121],"essential.":[19],"However,":[20],"stakeholder":[21],"comments":[22,63],"publicly":[24],"available":[25],"government":[26],"data":[27],"are":[28,101],"often":[29],"underutilized,":[30],"despite":[31],"their":[32],"potential":[33],"to":[34,89,124],"reveal":[35],"procedural":[36],"irregularities.":[37],"To":[38],"address":[39],"this":[40,42],"gap,":[41],"paper":[43],"analyzes":[44],"metadata":[45],"from":[46],"Ecuador's":[47],"Sistema":[48],"Oficial":[49],"de":[50],"Contrataci\u00f3n":[51],"P\u00fablica":[52],"(SOCE,":[53],"Official":[54],"Procurement":[56],"System),":[57],"with":[58],"particular":[59],"emphasis":[60],"on":[61],"participant":[62],"generated":[64,102],"during":[65],"pre-contractual":[67],"phase.":[68],"We":[69],"propose":[70],"a":[71,83,143],"hybrid":[72],"modeling":[73],"framework":[74],"that":[75,133,160],"integrates":[76],"unsupervised":[77,115],"clustering":[78],"supervised":[80,118],"classification":[81,119],"within":[82],"natural":[84],"language":[85],"processing":[86],"(NLP)":[87],"pipeline":[88],"uncover":[90],"latent":[91],"patterns":[92],"detect":[94],"potentially":[95],"irregular":[96],"processes.":[98],"Semantic":[99],"embeddings":[100],"using":[103],"Word2Vec,":[104],"LLaMA,":[105],"RoBERTa,":[107],"followed":[108],"by":[109],"Gaussian":[110],"Mixture":[111],"Models":[112],"(GMMs)":[113],"for":[114],"clustering.":[116],"A":[117],"stage":[120],"then":[122],"applied":[123],"identify":[125],"accusatory":[126],"or":[127],"whistleblowing-style":[128],"comments.":[129],"Experimental":[130],"results":[131],"show":[132],"combination":[135],"domain-trained":[137],"Word2Vec":[138],"embeddings,":[139],"GMM-based":[140],"clustering,":[141],"Random":[144],"Forest":[145],"classifier":[146],"achieves":[147],"high":[148],"precision":[149],"recall,":[151],"even":[152],"under":[153],"severe":[154],"class":[155],"imbalance.":[156],"These":[157],"findings":[158],"demonstrate":[159],"lightweight,":[161],"domain-adapted":[162],"NLP":[163],"architectures":[164],"can":[165],"effectively":[166],"support":[167],"risk":[168],"identification":[169],"enhance":[171],"transparency":[172],"in":[173],"public":[174],"systems":[176],"without":[177],"requiring":[178],"large-scale":[179],"computational":[180],"infrastructure.":[181]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-08-14T00:00:00"}