{"id":"https://openalex.org/W4206114143","doi":"https://doi.org/10.1109/tgrs.2022.3144666","title":"An Open-Source Package for Deep-Learning-Based Seismic Facies Classification: Benchmarking Experiments on the SEG 2020 Open Data","display_name":"An Open-Source Package for Deep-Learning-Based Seismic Facies Classification: Benchmarking Experiments on the SEG 2020 Open Data","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4206114143","doi":"https://doi.org/10.1109/tgrs.2022.3144666"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3144666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3144666","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005084143","display_name":"Xintao Chai","orcid":"https://orcid.org/0000-0002-1362-4491"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]},{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xintao Chai","raw_affiliation_strings":["OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), Beijing, China"],"affiliations":[{"raw_affiliation_string":"OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), Beijing, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112908814","display_name":"Wenhui Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Nie","raw_affiliation_strings":["OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005050835","display_name":"Kai Lin","orcid":"https://orcid.org/0000-0001-9631-3586"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Lin","raw_affiliation_strings":["OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083028659","display_name":"Genyang Tang","orcid":"https://orcid.org/0000-0003-1925-1304"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genyang Tang","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), Beijing, China","Engineering Research Center for Exploration and Development of Complex Oil/Gas Reservoir, Ministry of Education, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), Beijing, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"Engineering Research Center for Exploration and Development of Complex Oil/Gas Reservoir, Ministry of Education, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070230075","display_name":"Taihui Yang","orcid":"https://orcid.org/0000-0003-2981-3120"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Taihui Yang","raw_affiliation_strings":["OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083388590","display_name":"Junyong Yu","orcid":"https://orcid.org/0009-0006-0317-792X"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyong Yu","raw_affiliation_strings":["OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China"],"affiliations":[{"raw_affiliation_string":"OpenGEO Group, Consortium for Seismic Data Processing and Imaging (CSDPI), Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112075075","display_name":"Wenjun Cao","orcid":"https://orcid.org/0009-0004-5317-5434"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjun Cao","raw_affiliation_strings":["Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Deep Oil and Gas, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5005084143"],"corresponding_institution_ids":["https://openalex.org/I204553293","https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":5.2018,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.9667966,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.998199999332428,"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/T10892","display_name":"Drilling and Well Engineering","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8044015169143677},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7790865302085876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5774276256561279},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.539070188999176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.51240473985672},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47299084067344666},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.46459150314331055},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4509982764720917},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4394872784614563},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36012813448905945},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21873018145561218}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8044015169143677},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7790865302085876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5774276256561279},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.539070188999176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.51240473985672},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47299084067344666},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.46459150314331055},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4509982764720917},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4394872784614563},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36012813448905945},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21873018145561218},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3144666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3144666","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3719179096","display_name":null,"funder_award_id":"41704129","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4698310305","display_name":null,"funder_award_id":"11805166","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4993443379","display_name":null,"funder_award_id":"41774143","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G69910979","display_name":null,"funder_award_id":"CUGL180802","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8981404249","display_name":null,"funder_award_id":"PRP/open-2108","funder_id":"https://openalex.org/F4320321547","funder_display_name":"China University of Petroleum, Beijing"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321547","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12"},{"id":"https://openalex.org/F4320328899","display_name":"China University of Geosciences","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1522301498","https://openalex.org/W1901616594","https://openalex.org/W1910501430","https://openalex.org/W1973785137","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2605232094","https://openalex.org/W2769385952","https://openalex.org/W2771203173","https://openalex.org/W2785795994","https://openalex.org/W2807914764","https://openalex.org/W2891255706","https://openalex.org/W2891691398","https://openalex.org/W2894410771","https://openalex.org/W2899651173","https://openalex.org/W2900936384","https://openalex.org/W2904005001","https://openalex.org/W2912913790","https://openalex.org/W2923222994","https://openalex.org/W2928781249","https://openalex.org/W2947853264","https://openalex.org/W2963941635","https://openalex.org/W2970913068","https://openalex.org/W2972117744","https://openalex.org/W2977897970","https://openalex.org/W2979483515","https://openalex.org/W2982479281","https://openalex.org/W2984603160","https://openalex.org/W2990652904","https://openalex.org/W3001732295","https://openalex.org/W3007658705","https://openalex.org/W3009658940","https://openalex.org/W3011415648","https://openalex.org/W3012137738","https://openalex.org/W3014564255","https://openalex.org/W3033008664","https://openalex.org/W3034362861","https://openalex.org/W3038091703","https://openalex.org/W3081502560","https://openalex.org/W3092038435","https://openalex.org/W3094508212","https://openalex.org/W3102755745","https://openalex.org/W3112139896","https://openalex.org/W3119195183","https://openalex.org/W3125476449","https://openalex.org/W3127080376","https://openalex.org/W3130010174","https://openalex.org/W3147262955","https://openalex.org/W3197823310","https://openalex.org/W3198190168","https://openalex.org/W6631190155","https://openalex.org/W6786836634"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W2806031239","https://openalex.org/W2765476116","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295"],"abstract_inverted_index":{"Recently,":[0],"intelligent":[1],"data":[2,16,39,95],"processing":[3],"and":[4,36,42,159,165,204,212],"interpretation":[5],"based":[6],"on":[7,195],"deep":[8],"learning":[9],"(DL)":[10],"have":[11,25],"received":[12],"considerable":[13],"attention.":[14],"Training":[15],"are":[17,53,219,253],"vital":[18],"for":[19,40,82],"DL-based":[20,83],"approaches.":[21],"In":[22],"geosciences,":[23],"researchers":[24,156],"been":[26],"facing":[27],"a":[28,80,101,239],"significant":[29],"obstacle,":[30],"i.e.,":[31],"the":[32,55,61,64,93,97,112,119,123,131,183,196,210,217,225,229,249],"absence":[33],"of":[34,63,66,134,206,228],"authoritative":[35],"representative":[37],"open":[38,78],"training":[41,100,211],"testing":[43,213],"artificial":[44],"neural":[45],"networks":[46],"(ANNs).":[47],"Although":[48],"open-source":[49],"works":[50],"in":[51,168],"geosciences":[52],"increasing,":[54],"quantity":[56],"is":[57,141],"currently":[58],"limited.":[59],"With":[60],"aid":[62],"Society":[65],"Exploration":[67],"Geophysicists":[68],"(SEG)":[69],"2020":[70,198],"Machine":[71],"Learning":[72],"(ML)":[73],"Blind-Test":[74],"Challenge":[75,200],"Data,":[76],"we":[77,116,189,237],"source":[79],"package":[81],"seismic":[84,94],"facies":[85,98,208],"classification":[86],"(SFC).":[87],"We":[88,146,172],"regard":[89],"SFC":[90],"as":[91],"translating":[92],"into":[96],"by":[99,111,121],"flexible":[102,231],"end-to-end":[103,232],"encoding\u2013decoding-style":[104,233],"ANN":[105],"\u201cBridgeNet\u201d":[106],"revised":[107],"from":[108],"U-Net.":[109],"Inspired":[110],"residual":[113],"network":[114],"(ResNet),":[115],"further":[117],"enhance":[118],"BridgeNet":[120],"inserting":[122],"identity":[124],"shortcut":[125],"connections,":[126],"which":[127],"can":[128,150],"theoretically":[129],"ease":[130],"notorious":[132],"problem":[133],"vanishing/exploding":[135],"gradients.":[136],"The":[137,202,251],"evaluated":[138],"framework,":[139],"however,":[140],"not":[142],"restricted":[143],"to":[144,157,177,186,247],"SFC.":[145],"hope":[147],"that":[148,154,162,216],"it":[149],"provide":[151],"some":[152,179],"insights":[153],"help":[155],"construct":[158],"train":[160],"ANNs":[161],"yield":[163],"reliable":[164],"robust":[166],"results":[167,194,218],"their":[169],"own":[170],"tasks.":[171],"carry":[173],"out":[174],"benchmarking":[175],"experiments":[176],"investigate":[178],"crucial":[180],"factors":[181],"impacting":[182],"ANN\u2019s":[184],"performance":[185],"elucidate":[187],"how":[188],"obtained":[190],"our":[191],"current":[192],"optimal":[193],"SEG":[197],"ML":[199],"Data.":[201],"accuracy":[203],"continuity":[205],"predicted":[207],"along":[209],"sections":[214],"indicate":[215],"consistent":[220],"with":[221],"geologic":[222],"sedimentation,":[223],"verifying":[224],"generalization":[226],"capability":[227],"enhanced":[230],"BridgeNet.":[234],"For":[235],"SFC,":[236],"recommend":[238],"memory-saving":[240],"sparse":[241],"categorical":[242],"cross-entropy":[243],"(CC)":[244],"loss":[245],"function":[246],"improve":[248],"efficiency.":[250],"codes":[252],"available":[254],"at":[255],"<uri":[256],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[257],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://doi.org/10.5281/zenodo.5787673</uri>":[258],".":[259]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}