{"id":"https://openalex.org/W7155158317","doi":"https://doi.org/10.1016/j.jciso.2026.100179","title":"Explainable metaheuristic-optimized XGBoost models for accurate prediction of CO2 capture by graphene-based adsorbents","display_name":"Explainable metaheuristic-optimized XGBoost models for accurate prediction of CO2 capture by graphene-based adsorbents","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155158317","doi":"https://doi.org/10.1016/j.jciso.2026.100179"},"language":"en","primary_location":{"id":"doi:10.1016/j.jciso.2026.100179","doi":"https://doi.org/10.1016/j.jciso.2026.100179","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jciso.2026.100179","pdf_url":null,"source":{"id":"https://openalex.org/S4210231036","display_name":"JCIS Open","issn_l":"2666-934X","issn":["2666-934X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JCIS Open","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.jciso.2026.100179","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022252520","display_name":"Hamdi A. Al-Jamimi","orcid":"https://orcid.org/0000-0002-5100-1869","observed_orcids":["https://orcid.org/0000-0002-5100-1869"]},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Hamdi A. Al-Jamimi","raw_affiliation_strings":["Department of Information and Computer Science, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia","SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024285542","display_name":"Mohammed A.A. Elgzoly","orcid":"https://orcid.org/0000-0001-9368-5472","observed_orcids":["https://orcid.org/0000-0001-9368-5472"]},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohammed A.A. Elgzoly","raw_affiliation_strings":["Department of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087475730","display_name":"Sadam Al-Azani","orcid":"https://orcid.org/0000-0001-7893-1196","observed_orcids":["https://orcid.org/0000-0001-7893-1196"]},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Sadam Al-Azani","raw_affiliation_strings":["Department of Information and Computer Science, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia","SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Science, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRC-AI), King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083699619","display_name":"Sagheer A. Onaizi","orcid":"https://orcid.org/0000-0002-6674-4542","observed_orcids":["https://orcid.org/0000-0002-6674-4542"]},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Sagheer A. Onaizi","raw_affiliation_strings":["Department of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia","Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management, King Fahd University of Petroleum and Minerals, Dhahran 31216, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5083699619"],"corresponding_institution_ids":["https://openalex.org/I134085113"],"apc_list":{"value":1590,"currency":"USD","value_usd":1590},"apc_paid":{"value":1590,"currency":"USD","value_usd":1590},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21216507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"100179","last_page":"100179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10967","display_name":"Carbon Dioxide Capture Technologies","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10967","display_name":"Carbon Dioxide Capture Technologies","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.006800000090152025,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10016","display_name":"Adsorption and biosorption for pollutant removal","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/co2-capture","display_name":"CO2 capture","score":0.9039999842643738},{"id":"https://openalex.org/keywords/co2-adsorption","display_name":"CO2 adsorption","score":0.824999988079071},{"id":"https://openalex.org/keywords/graphene-based-adsorbents","display_name":"graphene-based adsorbents","score":0.9459999799728394},{"id":"https://openalex.org/keywords/reduced-graphene-oxide","display_name":"reduced graphene oxide","score":0.7799999713897705},{"id":"https://openalex.org/keywords/amine-functionalized-graphene-oxide","display_name":"amine-functionalized graphene oxide","score":0.9409999847412109},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.8259999752044678},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"differential evolution","score":0.9599999785423279},{"id":"https://openalex.org/keywords/metaheuristic-optimization","display_name":"metaheuristic optimization","score":0.8370000123977661},{"id":"https://openalex.org/keywords/explainable-machine-learning","display_name":"explainable machine learning","score":0.7599999904632568},{"id":"https://openalex.org/keywords/shap-analysis","display_name":"SHAP analysis","score":0.8560000061988831},{"id":"https://openalex.org/keywords/adsorption-capacity-prediction","display_name":"adsorption capacity prediction","score":0.8330000042915344}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6848000288009644},{"id":"https://openalex.org/C150394285","wikidata":"https://www.wikidata.org/wiki/Q180254","display_name":"Adsorption","level":2,"score":0.6560999751091003},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4952000081539154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4932999908924103},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4496999979019165},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C2777968448","wikidata":"https://www.wikidata.org/wiki/Q6964006","display_name":"Nanocellulose","level":3,"score":0.3878999948501587},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3693000078201294},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.3467999994754791},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3425000011920929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3314000070095062},{"id":"https://openalex.org/C60100273","wikidata":"https://www.wikidata.org/wiki/Q902806","display_name":"Thermogravimetric analysis","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.329800009727478},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.32510000467300415},{"id":"https://openalex.org/C92880739","wikidata":"https://www.wikidata.org/wiki/Q2639556","display_name":"Nanocomposite","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C150077022","wikidata":"https://www.wikidata.org/wiki/Q3136137","display_name":"Response surface methodology","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.3109000027179718},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2962999939918518},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C138631740","wikidata":"https://www.wikidata.org/wiki/Q967847","display_name":"Nanomaterials","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C3019413757","wikidata":"https://www.wikidata.org/wiki/Q56298528","display_name":"Co2 removal","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.259799987077713},{"id":"https://openalex.org/C140205800","wikidata":"https://www.wikidata.org/wiki/Q5860","display_name":"Carbon fibers","level":3,"score":0.25450000166893005},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.jciso.2026.100179","doi":"https://doi.org/10.1016/j.jciso.2026.100179","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jciso.2026.100179","pdf_url":null,"source":{"id":"https://openalex.org/S4210231036","display_name":"JCIS Open","issn_l":"2666-934X","issn":["2666-934X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JCIS Open","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a6e69deb279440bfacbc42db98d6f357","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/a6e69deb279440bfacbc42db98d6f357","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"JCIS Open, Vol 22, Iss , Pp 100179- (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.jciso.2026.100179","doi":"https://doi.org/10.1016/j.jciso.2026.100179","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jciso.2026.100179","pdf_url":null,"source":{"id":"https://openalex.org/S4210231036","display_name":"JCIS Open","issn_l":"2666-934X","issn":["2666-934X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"JCIS Open","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.9786999821662903,"id":"https://metadata.un.org/sdg/13"}],"sustainable_development_goals_aurora":[{"display_name":"Affordable and clean energy","score":0.8000849485397339,"id":"https://metadata.un.org/sdg/7"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322323","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1979099442","https://openalex.org/W1994310224","https://openalex.org/W2028323767","https://openalex.org/W2043449394","https://openalex.org/W2044110450","https://openalex.org/W2068534776","https://openalex.org/W2070577777","https://openalex.org/W2085192004","https://openalex.org/W2119140513","https://openalex.org/W2140746165","https://openalex.org/W2156194072","https://openalex.org/W2217038152","https://openalex.org/W2289948488","https://openalex.org/W2294371990","https://openalex.org/W2295598076","https://openalex.org/W2321266581","https://openalex.org/W2564781896","https://openalex.org/W2622719182","https://openalex.org/W2750158472","https://openalex.org/W2766585573","https://openalex.org/W2792314300","https://openalex.org/W2911351023","https://openalex.org/W2942998504","https://openalex.org/W3169203486","https://openalex.org/W3188319771","https://openalex.org/W4205497559","https://openalex.org/W4223450640","https://openalex.org/W4243150065","https://openalex.org/W4284970313","https://openalex.org/W4290078390","https://openalex.org/W4312857460","https://openalex.org/W4315567963","https://openalex.org/W4378803232","https://openalex.org/W4380324041","https://openalex.org/W4384789437","https://openalex.org/W4385253938","https://openalex.org/W4387623066","https://openalex.org/W4388968778","https://openalex.org/W4389304586","https://openalex.org/W4389817882","https://openalex.org/W4390937616","https://openalex.org/W4391116791","https://openalex.org/W4392202656","https://openalex.org/W4402622251","https://openalex.org/W4402878854","https://openalex.org/W4404280831","https://openalex.org/W4407861224","https://openalex.org/W4407932469","https://openalex.org/W4408305402","https://openalex.org/W4410946543","https://openalex.org/W4411125752","https://openalex.org/W4416794407"],"related_works":[],"abstract_inverted_index":{"The":[0,85,144],"continued":[1],"rise":[2],"in":[3,195],"atmospheric":[4],"CO":[5,27,79,93,212],"2":[6,28,80,94,153,213],"levels":[7],"is":[8,176,262],"a":[9,34,52,206,236],"leading":[10],"driver":[11],"of":[12,19,63,73,92,159,192,202,226],"global":[13,70],"climate":[14],"change,":[15],"necessitating":[16],"the":[17,60,69,120,177,190,198,223,245,254],"development":[18],"effective":[20],"carbon":[21],"capture":[22],"strategies.":[23],"Among":[24],"these,":[25],"adsorption-based":[26],"removal":[29,225],"using":[30,235,244],"engineered":[31],"nanomaterials":[32],"offers":[33],"promising":[35,207],"approach":[36],"due":[37],"to":[38,77,105,240],"its":[39],"energy":[40],"efficiency,":[41],"modularity,":[42],"and":[43,99,107,118,128,141,156,162,185,200,257],"tunable":[44],"surface":[45],"chemistry.":[46],"In":[47],"this":[48],"study,":[49],"we":[50],"present":[51],"hybrid":[53],"machine":[54,232,259],"learning":[55,233,260],"(ML)":[56],"framework":[57,209],"that":[58,173],"combines":[59],"predictive":[61],"accuracy":[62,199],"eXtreme":[64],"Gradient":[65],"Boosting":[66],"(XGBoost)":[67],"with":[68],"optimization":[71,194],"strength":[72],"Differential":[74],"Evolution":[75],"(DE)":[76],"model":[78,122,146,183],"uptake":[81],"by":[82],"graphene-based":[83],"adsorbents.":[84],"dataset,":[86],"derived":[87],"from":[88],"controlled":[89],"thermogravimetric":[90],"measurements":[91],"adsorption":[95,174,243],"onto":[96],"GO,":[97],"rGO,":[98],"amine-functionalized":[100],"GO":[101],"variants,":[102],"was":[103,123,228],"used":[104],"train":[106],"evaluate":[108],"multiple":[109],"ML":[110,130,203],"models.":[111],"Following":[112],"data":[113],"pre-processing,":[114],"including":[115,132],"feature":[116,180],"encoding":[117],"normalization,":[119],"DE-XGBoost":[121,145],"benchmarked":[124],"against":[125],"several":[126],"baseline":[127],"advanced":[129],"algorithms,":[131],"linear":[133],"regression,":[134],"multilayer":[135],"perceptron":[136],"(MLP),":[137],"random":[138],"forest":[139],"(RF),":[140],"non-optimized":[142],"XGBoost.":[143],"outperformed":[147],"all":[148],"other":[149,258],"approaches,":[150],"achieving":[151],"R":[152],",":[154],"RMSE,":[155],"MAE":[157],"values":[158],"0.986,1.9":[160],"mg/g,":[161,164],"1.2":[163],"respectively.":[165],"SHAP":[166],"(SHapley":[167],"Additive":[168],"exPlanations)":[169],"analysis":[170],"consistently":[171],"indicates":[172],"time":[175],"most":[178],"influential":[179],"across":[181],"different":[182],"settings":[184],"scenarios.":[186],"This":[187],"study":[188],"demonstrates":[189],"power":[191],"metaheuristic":[193],"enhancing":[196],"both":[197],"interpretability":[201],"models,":[204],"providing":[205],"data-driven":[208],"for":[210,222],"accelerating":[211],"adsorbent":[214],"performance":[215],"prediction.":[216],"\u2022":[217,230,250],"A":[218],"novel":[219],"PGB-LTH":[220],"nanocomposite":[221,247],"adsorptive":[224],"dyes":[227,242],"prepared":[229],"Ensemble":[231],"models":[234,256,261],"Decision":[237],"Trees":[238],"algorithm":[239],"predict":[241],"synthesized":[246],"were":[248],"developed.":[249],"Thorough":[251],"comparison":[252],"between":[253],"developed":[255],"provided.":[263]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-04-23T00:00:00"}