{"id":"https://openalex.org/W2037228647","doi":"https://doi.org/10.1109/tit.2014.2343629","title":"Hypothesis Testing in High-Dimensional Regression Under the Gaussian Random Design Model: Asymptotic Theory","display_name":"Hypothesis Testing in High-Dimensional Regression Under the Gaussian Random Design Model: Asymptotic Theory","publication_year":2014,"publication_date":"2014-07-28","ids":{"openalex":"https://openalex.org/W2037228647","doi":"https://doi.org/10.1109/tit.2014.2343629","mag":"2037228647"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2014.2343629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2014.2343629","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1301.4240","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010342958","display_name":"Adel Javanmard","orcid":"https://orcid.org/0000-0003-1934-8747"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Adel Javanmard","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University, Stanford, CA, USA","Department of Electrical Engineering, Stanford University Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011999109","display_name":"Andrea Montanari","orcid":"https://orcid.org/0000-0002-0267-8574"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea Montanari","raw_affiliation_strings":["Department of Statistics, Stanford University, Stanford, CA, USA","Department of Electrical Engineering, Stanford University Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010342958"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":3.3718,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.92581995,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"60","issue":"10","first_page":"6522","last_page":"6554"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9958999752998352,"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/mathematics","display_name":"Mathematics","score":0.7157153487205505},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7053404450416565},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6747719049453735},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.5746826529502869},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.516451358795166},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.51291823387146},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.49800777435302734},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.49581179022789},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.48163026571273804},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.42558589577674866},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.42517516016960144},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4131723642349243},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.36797064542770386},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36592987179756165},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3386072516441345},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.24106672406196594},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.16933032870292664},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10290411114692688}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7157153487205505},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7053404450416565},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6747719049453735},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.5746826529502869},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.516451358795166},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.51291823387146},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.49800777435302734},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.49581179022789},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.48163026571273804},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.42558589577674866},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.42517516016960144},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4131723642349243},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.36797064542770386},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36592987179756165},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3386072516441345},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.24106672406196594},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.16933032870292664},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10290411114692688},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tit.2014.2343629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2014.2343629","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1301.4240","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1301.4240","pdf_url":"https://arxiv.org/pdf/1301.4240","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2037228647","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1301.4240","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1301.4240","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1301.4240","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1301.4240","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1301.4240","pdf_url":"https://arxiv.org/pdf/1301.4240","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6329851102","display_name":null,"funder_award_id":"FA9550-12-1-0411","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G6331703163","display_name":null,"funder_award_id":"FA9550-10-1-0360","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2037228647.pdf"},"referenced_works_count":85,"referenced_works":["https://openalex.org/W108633999","https://openalex.org/W132471885","https://openalex.org/W1479807131","https://openalex.org/W1485215434","https://openalex.org/W1572652170","https://openalex.org/W1573820523","https://openalex.org/W1605482898","https://openalex.org/W1716904016","https://openalex.org/W1971565000","https://openalex.org/W1977031875","https://openalex.org/W1989727964","https://openalex.org/W2008997396","https://openalex.org/W2010669260","https://openalex.org/W2010824638","https://openalex.org/W2023982864","https://openalex.org/W2034260606","https://openalex.org/W2042542290","https://openalex.org/W2045638068","https://openalex.org/W2050556604","https://openalex.org/W2067038358","https://openalex.org/W2069119359","https://openalex.org/W2071168995","https://openalex.org/W2077306951","https://openalex.org/W2078411132","https://openalex.org/W2082029531","https://openalex.org/W2090842051","https://openalex.org/W2092058109","https://openalex.org/W2097209031","https://openalex.org/W2101435685","https://openalex.org/W2103001925","https://openalex.org/W2108275041","https://openalex.org/W2115275122","https://openalex.org/W2116394223","https://openalex.org/W2116581043","https://openalex.org/W2117577039","https://openalex.org/W2118902885","https://openalex.org/W2120383799","https://openalex.org/W2123202508","https://openalex.org/W2127300249","https://openalex.org/W2130351130","https://openalex.org/W2135046866","https://openalex.org/W2137198385","https://openalex.org/W2138358551","https://openalex.org/W2139053635","https://openalex.org/W2144015943","https://openalex.org/W2146653613","https://openalex.org/W2150940164","https://openalex.org/W2154972590","https://openalex.org/W2160955696","https://openalex.org/W2160968730","https://openalex.org/W2161410247","https://openalex.org/W2162312215","https://openalex.org/W2164595191","https://openalex.org/W2166670884","https://openalex.org/W2170929819","https://openalex.org/W2550925785","https://openalex.org/W2562162676","https://openalex.org/W2566505556","https://openalex.org/W2949204716","https://openalex.org/W2949779502","https://openalex.org/W2949884817","https://openalex.org/W2949901676","https://openalex.org/W2951271920","https://openalex.org/W2951767789","https://openalex.org/W2953013062","https://openalex.org/W2962726112","https://openalex.org/W2964253263","https://openalex.org/W2964312599","https://openalex.org/W2965497096","https://openalex.org/W3098834468","https://openalex.org/W3098848552","https://openalex.org/W3099550161","https://openalex.org/W3101710166","https://openalex.org/W3101788651","https://openalex.org/W3105340263","https://openalex.org/W4205806204","https://openalex.org/W4210422269","https://openalex.org/W6634225129","https://openalex.org/W6667239768","https://openalex.org/W6673293446","https://openalex.org/W6679265385","https://openalex.org/W6682241100","https://openalex.org/W6683449525","https://openalex.org/W6683664273","https://openalex.org/W6729847528"],"related_works":["https://openalex.org/W2135046866","https://openalex.org/W3098834468","https://openalex.org/W2116581043","https://openalex.org/W3099550161","https://openalex.org/W2154972590","https://openalex.org/W2127300249","https://openalex.org/W3103643510","https://openalex.org/W2152204644","https://openalex.org/W2150940164","https://openalex.org/W2128235479","https://openalex.org/W340056678","https://openalex.org/W3121832289","https://openalex.org/W3105340263","https://openalex.org/W2092058109","https://openalex.org/W2074682976","https://openalex.org/W2069119359","https://openalex.org/W2063978378","https://openalex.org/W2020925091","https://openalex.org/W3104399671","https://openalex.org/W2898206519"],"abstract_inverted_index":{"We":[0,127,228],"consider":[1,82],"linear":[2],"regression":[3,105],"in":[4,26,143,162,336],"the":[5,9,17,36,51,55,69,84,98,117,147,163,180,191,195,216,293,321,333,346,353],"high-dimensional":[6],"regime":[7],"where":[8],"number":[10,18],"of":[11,19,43,62,91,100,120,165,179,190,194,218,310,352,360],"observations":[12],"n":[13,46,211,262,306],"is":[14,155,174,212,275],"smaller":[15],"than":[16,265,345],"parameters":[20,47,57],"p.":[21],"A":[22],"very":[23],"successful":[24],"approach":[25,173,231],"this":[27,76,79,140,152,247],"setting":[28,54],"uses":[29],"11-penalized":[30],"least":[31,214,309],"squares":[32],"(also":[33],"known":[34],"as":[35],"Lasso)":[37],"to":[38,58,67,138,232],"search":[39],"for":[40,103,132,205,261,287,302,325,356],"a":[41,112,123,159,177,187,252,284,342,357],"subset":[42],"s0":[44],"<;":[45],"that":[48,129,151,251,301],"best":[49],"explain":[50],"data,":[52],"while":[53],"other":[56],"zero.":[59],"Considerable":[60],"amount":[61],"work":[63],"has":[64],"been":[65],"devoted":[66],"characterizing":[68],"estimation":[70],"and":[71,198,291,350],"model":[72],"selection":[73],"problems":[74],"within":[75],"approach.":[77],"In":[78,246],"paper,":[80],"we":[81,96,110,149,249,282,299,348],"instead":[83],"fundamental,":[85],"but":[86],"far":[87],"less":[88],"understood,":[89],"question":[90],"statistical":[92,337,354],"significance.":[93],"More":[94],"precisely,":[95],"address":[97],"problem":[99],"computing":[101],"p-values":[102],"single":[104],"coefficients.":[106],"On":[107,146],"one":[108],"hand,":[109],"develop":[111],"general":[113,326],"upper":[114,153],"bound":[115,154],"on":[116,176,186,215],"minimax":[118],"power":[119,355],"tests":[121],"with":[122,169,236,279],"given":[124],"significance":[125],"level.":[126],"show":[128,300],"rigorous":[130,188],"guarantees":[131],"earlier":[133],"methods":[134],"do":[135],"not":[136],"allow":[137],"achieve":[139],"bound,":[141],"except":[142],"special":[144],"cases.":[145],"other,":[148],"prove":[150,250],"(nearly)":[156],"achievable":[157],"through":[158,295],"practical":[160],"procedure":[161],"case":[164],"random":[166,233],"design":[167,234],"matrices":[168,235],"independent":[170,237],"entries.":[171],"Our":[172,202],"based":[175],"debiasing":[178],"Lasso":[181,196],"estimator.":[182],"The":[183],"analysis":[184,272],"builds":[185],"characterization":[189,255],"asymptotic":[192],"distribution":[193],"estimator":[197,286],"its":[199],"debiased":[200],"version.":[201],"result":[203,347],"holds":[204,260],"optimal":[206,303],"sample":[207,304],"size,":[208,305],"i.e.,":[209],"when":[210],"at":[213,308],"order":[217,311],"s":[219,312],"<sub":[220,224,313,317],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[221,225,269,314,318],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sub>":[222,226,315,319],"log(p/s":[223,316],").":[227],"generalize":[229],"our":[230],"identically":[238],"distributed":[239],"Gaussian":[240,327,361],"rows":[241],"xi":[242],"~":[243],"N(0,":[244],"\u03a3).":[245],"case,":[248],"similar":[253],"distributional":[254,258,323],"(termed":[256],"standard":[257,322],"limit)":[259],"much":[263],"larger":[264],"s0(log":[266],"p)":[267],"<sup":[268],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[270],".Our":[271],"assumes":[273],"\u03a3":[274,290],"known.":[276],"To":[277],"cope":[278],"unknown":[280],"\u03a3,":[281],"suggest":[283],"plug-in":[285],"sparse":[288],"covariances":[289],"validate":[292],"method":[294],"numerical":[296],"simulations.":[297],"Finally,":[298],"being":[307],"),":[320],"limit":[324],"designs":[328],"can":[329],"be":[330],"derived":[331],"from":[332],"replica":[334],"heuristics":[335],"physics.":[338],"This":[339],"derivation":[340],"suggests":[341],"stronger":[343],"conjecture":[344],"prove,":[349],"near-optimality":[351],"large":[358],"class":[359],"designs.":[362]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":5}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
