{"id":"https://openalex.org/W2080179517","doi":"https://doi.org/10.1109/tkde.2014.2327022","title":"Holistic Measures for Evaluating Prediction Models in Smart Grids","display_name":"Holistic Measures for Evaluating Prediction Models in Smart Grids","publication_year":2014,"publication_date":"2014-05-30","ids":{"openalex":"https://openalex.org/W2080179517","doi":"https://doi.org/10.1109/tkde.2014.2327022","mag":"2080179517"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2014.2327022","doi":"https://doi.org/10.1109/tkde.2014.2327022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2327022","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","fnege-3","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1406.0223","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Saima Aman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saima Aman","raw_affiliation_strings":["Department of Computer Science, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041794289","display_name":"Yogesh L. Simmhan","orcid":"https://orcid.org/0000-0003-4140-7774","observed_orcids":["https://orcid.org/0000-0003-4140-7774"]},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yogesh Simmhan","raw_affiliation_strings":["Indian Institute of Science, Bangaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Science, Bangaluru, India","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":null,"display_name":"Viktor K. Prasanna","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viktor K. Prasanna","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":3.7956,"has_fulltext":true,"cited_by_count":59,"citation_normalized_percentile":{"value":0.93787336,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"27","issue":"2","first_page":"475","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9506999850273132,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9506999850273132,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10603","display_name":"Smart Grid Energy Management","score":0.029899999499320984,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11918","display_name":"Forecasting Techniques and Applications","score":0.0026000000070780516,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prediction-model-evaluation","display_name":"prediction model evaluation","score":0.9610000252723694},{"id":"https://openalex.org/keywords/performance-indicators","display_name":"performance indicators","score":0.7570000290870667},{"id":"https://openalex.org/keywords/smart-grid","display_name":"smart grid","score":0.8069999814033508},{"id":"https://openalex.org/keywords/load-forecasting","display_name":"load forecasting","score":0.9330000281333923},{"id":"https://openalex.org/keywords/scale-independence","display_name":"scale independence","score":0.8059999942779541},{"id":"https://openalex.org/keywords/reliability-statistics","display_name":"reliability statistics","score":0.8309999704360962},{"id":"https://openalex.org/keywords/volatility","display_name":"volatility","score":0.9729999899864197},{"id":"https://openalex.org/keywords/cost","display_name":"cost","score":0.7570000290870667},{"id":"https://openalex.org/keywords/demand-response","display_name":"demand response","score":0.7960000038146973},{"id":"https://openalex.org/keywords/energy-planning","display_name":"energy planning","score":0.578000009059906},{"id":"https://openalex.org/keywords/customer-education","display_name":"client education","score":0.953000009059906},{"id":"https://openalex.org/keywords/model-selection","display_name":"model selection","score":0.503000020980835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79339998960495},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.6610999703407288},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.6341999769210815},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6169999837875366},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5479999780654907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5382999777793884},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.47920000553131104},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.46700000762939453},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41609999537467957},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4099000096321106},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C133199616","wikidata":"https://www.wikidata.org/wiki/Q25386885","display_name":"Empirical modelling","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C2779438525","wikidata":"https://www.wikidata.org/wiki/Q5255048","display_name":"Demand response","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.25929999351501465},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/tkde.2014.2327022","doi":"https://doi.org/10.1109/tkde.2014.2327022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2327022","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","fnege-3","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:eprints.iisc.ac.in:50791","doi":null,"is_oa":false,"landing_page_url":"http://eprints.iisc.ac.in/50791/1/iee_tra_kno_dat_eng_27-2_475_2014.pdf","pdf_url":"http://eprints.iisc.ac.in/50791/1/iee_tra_kno_dat_eng_27-2_475_2014.pdf","source":{"id":"https://openalex.org/S4377196309","display_name":"NOT FOUND REPOSITORY (Indian Institute of Science Bangalore)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"pmh:oai:arXiv.org:1406.0223","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1406.0223","pdf_url":"https://arxiv.org/pdf/1406.0223","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.707.9877","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.707.9877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://serc.iisc.ernet.in/%7Esimmhan/pubs/aman-tkde-2014.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.747.893","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.747.893","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1406.0223.pdf","raw_type":"text"},{"id":"doi:10.48550/arxiv.1406.0223","doi":"https://doi.org/10.48550/arxiv.1406.0223","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1406.0223","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1406.0223","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1406.0223","pdf_url":"https://arxiv.org/pdf/1406.0223","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.878000020980835,"display_name":"Affordable and clean energy"},{"id":"https://metadata.un.org/sdg/9","score":0.5378999710083008,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G4300979287","display_name":"TAS::89 0328::TAS RECOVERY - LADWP SMART GRID REGIONAL DEMONSTRATION PROJECT IN COLLABORATION WITH THE LA AREA UNIVERSITY CONSORTIUM","funder_award_id":"DEOE0000192","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2080179517.pdf","grobid_xml":"https://content.openalex.org/works/W2080179517.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W172260869","https://openalex.org/W1524073954","https://openalex.org/W1572134200","https://openalex.org/W1594031697","https://openalex.org/W1754293002","https://openalex.org/W1813011526","https://openalex.org/W1880076869","https://openalex.org/W1975877043","https://openalex.org/W1995027390","https://openalex.org/W1999148066","https://openalex.org/W2000548672","https://openalex.org/W2008084603","https://openalex.org/W2016210396","https://openalex.org/W2038849095","https://openalex.org/W2049751389","https://openalex.org/W2050529187","https://openalex.org/W2056859463","https://openalex.org/W2079682888","https://openalex.org/W2084724629","https://openalex.org/W2093290362","https://openalex.org/W2102739522","https://openalex.org/W2116174583","https://openalex.org/W2116512828","https://openalex.org/W2117825288","https://openalex.org/W2120194796","https://openalex.org/W2135846084","https://openalex.org/W2145725672","https://openalex.org/W2146097858","https://openalex.org/W2149301382","https://openalex.org/W2168138569","https://openalex.org/W2185171289","https://openalex.org/W2292360095","https://openalex.org/W2313953460","https://openalex.org/W2330820318","https://openalex.org/W2536023776","https://openalex.org/W2950037719","https://openalex.org/W3020789893","https://openalex.org/W3085162807","https://openalex.org/W6638332006"],"related_works":["https://openalex.org/W7095183772","https://openalex.org/W6964220896","https://openalex.org/W2026409976","https://openalex.org/W4321352795","https://openalex.org/W2283470002","https://openalex.org/W3042972169","https://openalex.org/W4399427322","https://openalex.org/W7116913079","https://openalex.org/W2913886569","https://openalex.org/W3036502021"],"abstract_inverted_index":{"The":[0],"performance":[1,41,65],"of":[2,31,56,64,74,142],"prediction":[3,32,47],"models":[4,33,48,70],"is":[5],"often":[6],"based":[7],"on":[8,157],"\u201cabstract":[9],"metrics\u201d":[10],"that":[11],"estimate":[12],"the":[13,21,51,72,89,140,143],"model's":[14],"ability":[15],"to":[16,67,92,98,107,146],"limit":[17],"residual":[18],"errors":[19],"between":[20],"observed":[22],"and":[23,29,39,79,86,128,154,166],"predicted":[24],"values.":[25],"However,":[26],"meaningful":[27],"evaluation":[28],"selection":[30],"for":[34,120,134],"end-user":[35],"domains":[36],"requires":[37],"holistic":[38],"application-sensitive":[40],"measures.":[42],"Inspired":[43],"by":[44,95],"energy":[45,117,135],"consumption":[46],"used":[49],"in":[50],"emerging":[52],"\u201cbig":[53],"data\u201d":[54],"domain":[55,96],"Smart":[57,122],"Power":[58],"Grids,":[59],"we":[60,110],"propose":[61],"a":[62,148],"suite":[63],"measures":[66,104,145],"rationally":[68],"compare":[69],"along":[71],"dimensions":[73],"scale":[75],"independence,":[76],"reliability,":[77],"volatility":[78],"cost.":[80],"We":[81],"include":[82],"both":[83,162],"application":[84],"independent":[85],"dependent":[87],"measures,":[88],"latter":[90],"parameterized":[91],"allow":[93],"customization":[94],"experts":[97],"fit":[99],"their":[100,155],"scenario.":[101],"While":[102],"our":[103],"are":[105,132],"generalizable":[106],"other":[108],"domains,":[109],"offer":[111,147],"an":[112],"empirical":[113],"analysis":[114],"using":[115],"real":[116,158],"use":[118],"data":[119,163],"three":[121],"Grid":[123],"applications:":[124],"planning,":[125],"customer":[126],"education":[127],"demand":[129],"response,":[130],"which":[131,160],"relevant":[133],"sustainability.":[136],"Our":[137],"results":[138],"underscore":[139],"value":[141],"proposed":[144],"deeper":[149],"insight":[150],"into":[151],"models'":[152],"behavior":[153],"impact":[156],"applications,":[159],"benefit":[161],"mining":[164],"researchers":[165],"practitioners.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
