{"id":"https://openalex.org/W4386608500","doi":"https://doi.org/10.1080/10618600.2023.2257258","title":"Clustering Sequence Data with Mixture Markov Chains with Covariates Using Multiple Simplex Constrained Optimization Routine (MSiCOR)","display_name":"Clustering Sequence Data with Mixture Markov Chains with Covariates Using Multiple Simplex Constrained Optimization Routine (MSiCOR)","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386608500","doi":"https://doi.org/10.1080/10618600.2023.2257258","pmid":"https://pubmed.ncbi.nlm.nih.gov/39877291"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2023.2257258","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2023.2257258","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11774513/pdf/nihms-2035084.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007525600","display_name":"Priyam Das","orcid":"https://orcid.org/0000-0003-2384-0486"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Priyam Das","raw_affiliation_strings":["Department of Biostatistics, Virginia Commonwealth University, Richmond, VA"],"raw_orcid":"https://orcid.org/0000-0003-2384-0486","affiliations":[{"raw_affiliation_string":"Department of Biostatistics, Virginia Commonwealth University, Richmond, VA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039011493","display_name":"Deborshee Sen","orcid":"https://orcid.org/0000-0001-9590-5416"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Deborshee Sen","raw_affiliation_strings":["Department of Mathematical Sciences, University of Bath, Bath, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Bath, Bath, UK","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065580944","display_name":"Debsurya De","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debsurya De","raw_affiliation_strings":["Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007063265","display_name":"Jue Hou","orcid":"https://orcid.org/0000-0002-9015-1827"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jue Hou","raw_affiliation_strings":["Department of Biostatistics, University of Minnesota, Minneapolis, MN"],"raw_orcid":"https://orcid.org/0000-0002-9015-1827","affiliations":[{"raw_affiliation_string":"Department of Biostatistics, University of Minnesota, Minneapolis, MN","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065817536","display_name":"Zahra S. H. Abad","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zahra S. H. Abad","raw_affiliation_strings":["Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082370114","display_name":"Nicole Kim","orcid":"https://orcid.org/0000-0002-4560-8808"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicole Kim","raw_affiliation_strings":["Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069572535","display_name":"Zongqi Xia","orcid":"https://orcid.org/0000-0003-1500-2589"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zongqi Xia","raw_affiliation_strings":["Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA","Department of Neurology, University of Pittsburgh, Pittsburgh, PA"],"raw_orcid":"https://orcid.org/0000-0003-1500-2589","affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"Department of Neurology, University of Pittsburgh, Pittsburgh, PA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078003862","display_name":"Tianxi Cai","orcid":"https://orcid.org/0000-0002-5379-2502"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianxi Cai","raw_affiliation_strings":["Department of Biomedical Informatics, Harvard Medical School, Boston, MA","Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA"],"raw_orcid":"https://orcid.org/0000-0002-5379-2502","affiliations":[{"raw_affiliation_string":"Department of Biomedical Informatics, Harvard Medical School, Boston, MA","institution_ids":["https://openalex.org/I136199984"]},{"raw_affiliation_string":"Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5007525600"],"corresponding_institution_ids":["https://openalex.org/I184840846"],"apc_list":null,"apc_paid":null,"fwci":0.5112,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71734563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"33","issue":"2","first_page":"379","last_page":"392"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9939000010490417,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9939000010490417,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9513999819755554,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6291900873184204},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5784186124801636},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5520164370536804},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.55112624168396},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5078116059303284},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.46653062105178833},{"id":"https://openalex.org/keywords/simplex","display_name":"Simplex","score":0.4558003544807434},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.450607031583786},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4172438979148865},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3772861361503601},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3755342662334442},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2987230718135834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29798781871795654},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2960038185119629},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19126734137535095},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.14805898070335388}],"concepts":[{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6291900873184204},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5784186124801636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5520164370536804},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.55112624168396},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5078116059303284},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.46653062105178833},{"id":"https://openalex.org/C62438384","wikidata":"https://www.wikidata.org/wiki/Q331350","display_name":"Simplex","level":2,"score":0.4558003544807434},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.450607031583786},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4172438979148865},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3772861361503601},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3755342662334442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2987230718135834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29798781871795654},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2960038185119629},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19126734137535095},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.14805898070335388},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/10618600.2023.2257258","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2023.2257258","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmid:39877291","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39877291","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11774513","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11774513","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11774513/pdf/nihms-2035084.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Comput Graph Stat","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11774513","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11774513","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11774513/pdf/nihms-2035084.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Comput Graph Stat","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3344279735","display_name":null,"funder_award_id":"R01NS124882","funder_id":"https://openalex.org/F4320337359","funder_display_name":"National Institute of Neurological Disorders and Stroke"},{"id":"https://openalex.org/G696712204","display_name":null,"funder_award_id":"R01NS098023","funder_id":"https://openalex.org/F4320337359","funder_display_name":"National Institute of Neurological Disorders and Stroke"}],"funders":[{"id":"https://openalex.org/F4320337359","display_name":"National Institute of Neurological Disorders and Stroke","ror":"https://ror.org/01s5ya894"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386608500.pdf"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W615245259","https://openalex.org/W1561348124","https://openalex.org/W1588749883","https://openalex.org/W1914444904","https://openalex.org/W1975292844","https://openalex.org/W1982087768","https://openalex.org/W2016670346","https://openalex.org/W2024060531","https://openalex.org/W2030723843","https://openalex.org/W2054875385","https://openalex.org/W2066319437","https://openalex.org/W2066334462","https://openalex.org/W2071563913","https://openalex.org/W2072863153","https://openalex.org/W2093634205","https://openalex.org/W2109364787","https://openalex.org/W2114521013","https://openalex.org/W2119401655","https://openalex.org/W2123037532","https://openalex.org/W2125656488","https://openalex.org/W2136486905","https://openalex.org/W2151363206","https://openalex.org/W2152195021","https://openalex.org/W2152710595","https://openalex.org/W2158378303","https://openalex.org/W2162064184","https://openalex.org/W2168175751","https://openalex.org/W2185708910","https://openalex.org/W2463089998","https://openalex.org/W2525708074","https://openalex.org/W2534222797","https://openalex.org/W2550626811","https://openalex.org/W2594899909","https://openalex.org/W2606339429","https://openalex.org/W2747530650","https://openalex.org/W2757339698","https://openalex.org/W2794568554","https://openalex.org/W2890491191","https://openalex.org/W2948544361","https://openalex.org/W2969316768","https://openalex.org/W2974419472","https://openalex.org/W3014962471","https://openalex.org/W3026375948","https://openalex.org/W3079330638","https://openalex.org/W3084224546","https://openalex.org/W3133027118","https://openalex.org/W3180651263","https://openalex.org/W3208184425","https://openalex.org/W3213676036","https://openalex.org/W4249877154","https://openalex.org/W4306790221","https://openalex.org/W4379157424","https://openalex.org/W6729343340"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W2153238387","https://openalex.org/W4312864369","https://openalex.org/W84255947","https://openalex.org/W2014842417","https://openalex.org/W2502114474","https://openalex.org/W2061347451"],"abstract_inverted_index":{"Mixture":[0],"Markov":[1],"Model":[2],"(MMM)":[3],"is":[4,52,90,98,113,131],"a":[5,16,72,85,151],"widely":[6],"used":[7,92],"tool":[8],"to":[9,42,93,100,115,133,154],"cluster":[10,134,155],"sequences":[11,143],"of":[12,37,49,87,124,144,186],"events":[13],"coming":[14],"from":[15],"finite":[17],"state-space.":[18],"However,":[19],"the":[20,25,38,44,57,62,66,110,117,122,174,193],"MMM":[21,45,95,125,169],"likelihood":[22,64],"being":[23],"multi-modal,":[24],"challenge":[26],"remains":[27,35],"in":[28,60,121],"its":[29],"maximization.":[30],"Although":[31],"Expectation-Maximization":[32],"(EM)":[33,119],"algorithm":[34,51,120],"one":[36],"most":[39],"popular":[40],"ways":[41],"estimate":[43],"parameters,":[46],"however,":[47],"convergence":[48],"EM":[50],"not":[53],"always":[54],"guaranteed.":[55],"Given":[56],"computational":[58],"challenges":[59],"maximizing":[61],"mixture":[63],"on":[65,84,140,160,173],"constrained":[67],"parameter":[68],"space,":[69],"we":[70,176],"develop":[71],"pattern":[73],"search-based":[74],"global":[75,104],"optimization":[76,105],"technique":[77],"which":[78,89],"can":[79],"optimize":[80],"any":[81],"objective":[82],"function":[83],"collection":[86],"simplexes,":[88],"eventually":[91],"maximize":[94],"likelihood.":[96],"This":[97],"shown":[99,114],"outperform":[101,116],"other":[102],"related":[103],"techniques.":[106],"In":[107],"simulation":[108],"experiments,":[109],"proposed":[111,129],"method":[112,130,153],"expectation-maximization":[118],"context":[123],"estimation":[126],"performance.":[127],"The":[128],"applied":[132],"Multiple":[135],"sclerosis":[136],"(MS)":[137],"patients":[138,179],"based":[139,159],"their":[141],"treatment":[142],"disease-modifying":[145],"therapies":[146],"(DMTs).":[147],"We":[148],"also":[149],"propose":[150],"novel":[152],"people":[156],"with":[157,170],"MS":[158,178],"DMT":[161],"prescriptions":[162],"and":[163],"associated":[164],"clinical":[165],"features":[166],"(covariates)":[167],"using":[168],"covariates.":[171],"Based":[172],"analysis,":[175],"divided":[177],"into":[180],"three":[181],"clusters.":[182,194],"Further":[183],"cluster-specific":[184],"summaries":[185],"relevant":[187],"covariates":[188],"indicate":[189],"patient":[190],"differences":[191],"among":[192],"Supplementary":[195],"materials":[196],"for":[197],"this":[198],"article":[199],"are":[200],"available":[201],"online.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
