{"id":"https://openalex.org/W2791062716","doi":"https://doi.org/10.1109/tits.2019.2923319","title":"Intentions of Vulnerable Road Users\u2014Detection and Forecasting by Means of Machine Learning","display_name":"Intentions of Vulnerable Road Users\u2014Detection and Forecasting by Means of Machine Learning","publication_year":2019,"publication_date":"2019-06-27","ids":{"openalex":"https://openalex.org/W2791062716","doi":"https://doi.org/10.1109/tits.2019.2923319","mag":"2791062716"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2923319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2923319","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","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/1803.03577","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043217442","display_name":"Michael Goldhammer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Goldhammer","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101723394","display_name":"Sebastian K\u00f6hler","orcid":"https://orcid.org/0000-0002-2261-5255"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sebastian Kohler","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-2261-5255","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086864323","display_name":"Stefan Zernetsch","orcid":"https://orcid.org/0000-0003-2016-5059"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Zernetsch","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0003-2016-5059","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047844917","display_name":"Konrad Doll","orcid":"https://orcid.org/0000-0002-3746-2319"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Konrad Doll","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-3746-2319","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065340030","display_name":"Bernhard Sick","orcid":"https://orcid.org/0000-0001-9467-656X"},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Sick","raw_affiliation_strings":["Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany","[Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]},{"raw_affiliation_string":"[Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany]","institution_ids":["https://openalex.org/I106157433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085054529","display_name":"Klaus Dietmayer","orcid":"https://orcid.org/0000-0002-1651-014X"},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Dietmayer","raw_affiliation_strings":["Institute of Measurement Control and Microtechnology, Ulm University, Ulm, Germany","Institute of Measurement, Control and Microtechnology Ulm University Ulm Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Measurement Control and Microtechnology, Ulm University, Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]},{"raw_affiliation_string":"Institute of Measurement, Control and Microtechnology Ulm University Ulm Germany","institution_ids":["https://openalex.org/I196349391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6166,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7054572,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"21","issue":"7","first_page":"3035","last_page":"3045"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10370","display_name":"Traffic and Road Safety","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.7075552940368652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.682096004486084},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6511900424957275},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.647972047328949},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.602923572063446},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5816623568534851},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5494680404663086},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5412070751190186},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5000350475311279},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.49481791257858276},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4853776693344116},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4609636962413788},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4338573217391968},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1467638909816742}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075552940368652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.682096004486084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6511900424957275},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.647972047328949},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.602923572063446},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5816623568534851},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5494680404663086},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5412070751190186},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5000350475311279},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.49481791257858276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4853776693344116},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4609636962413788},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4338573217391968},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1467638909816742},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tits.2019.2923319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2923319","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1803.03577","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.03577","pdf_url":"https://arxiv.org/pdf/1803.03577","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:2791062716","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1803.03577","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.1803.03577","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1803.03577","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1803.03577","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.03577","pdf_url":"https://arxiv.org/pdf/1803.03577","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":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4797834352","display_name":null,"funder_award_id":"03FH021I3","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"},{"id":"https://openalex.org/G7048914741","display_name":null,"funder_award_id":"DO 1186/1-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G7750906446","display_name":null,"funder_award_id":"SI 674/11-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2791062716.pdf","grobid_xml":"https://content.openalex.org/works/W2791062716.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1531532259","https://openalex.org/W1579387951","https://openalex.org/W1936415111","https://openalex.org/W1937999893","https://openalex.org/W1954601274","https://openalex.org/W1970490026","https://openalex.org/W1982230942","https://openalex.org/W1996133250","https://openalex.org/W2004641798","https://openalex.org/W2028158532","https://openalex.org/W2031638733","https://openalex.org/W2035057357","https://openalex.org/W2091707830","https://openalex.org/W2101415982","https://openalex.org/W2103873528","https://openalex.org/W2121511604","https://openalex.org/W2126413547","https://openalex.org/W2142704643","https://openalex.org/W2143908786","https://openalex.org/W2150823086","https://openalex.org/W2152873711","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2164685708","https://openalex.org/W2197015301","https://openalex.org/W2238582461","https://openalex.org/W2286744228","https://openalex.org/W2424778531","https://openalex.org/W2492863842","https://openalex.org/W2513866924","https://openalex.org/W2532853997","https://openalex.org/W2565986202","https://openalex.org/W2740801047","https://openalex.org/W2964193755","https://openalex.org/W6737845821"],"related_works":["https://openalex.org/W2962783540","https://openalex.org/W3160291349","https://openalex.org/W2897623894","https://openalex.org/W3000378996","https://openalex.org/W2989917634","https://openalex.org/W1591897158","https://openalex.org/W1899908593","https://openalex.org/W2807456624","https://openalex.org/W3086118399","https://openalex.org/W3116669292","https://openalex.org/W2565719461","https://openalex.org/W2980695382","https://openalex.org/W3129932917","https://openalex.org/W2042929057","https://openalex.org/W3154724615","https://openalex.org/W3166288215","https://openalex.org/W2800381837","https://openalex.org/W3211686163","https://openalex.org/W2785915306","https://openalex.org/W3200533894"],"abstract_inverted_index":{"Avoiding":[0],"collisions":[1],"with":[2],"vulnerable":[3],"road":[4],"users":[5],"(VRUs)":[6],"using":[7],"sensor-based":[8],"early":[9],"recognition":[10],"of":[11,16,28,43,87,100,137,140,159,188,206],"critical":[12],"situations":[13],"is":[14,117,152],"one":[15],"the":[17,22,26,77,84,88,98,115,160,171,174,186],"manifold":[18],"opportunities":[19],"provided":[20],"by":[21,185],"current":[23,78],"development":[24],"in":[25,49,68,73],"field":[27],"intelligent":[29],"vehicles.":[30],"As,":[31],"especially,":[32],"pedestrians":[33],"and":[34,39,81,126,128,143,157,170,212,219],"cyclists":[35],"are":[36,93,215],"very":[37],"agile":[38],"have":[40],"a":[41,53,107,138],"variety":[42],"movement":[44,61],"options,":[45],"modeling":[46],"their":[47],"behavior":[48],"traffic":[50],"scenes":[51,146],"becomes":[52],"challenging":[54],"task.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59],"propose":[60],"models":[62,123],"based":[63,105],"on":[64,106,226],"machine":[65,175],"learning":[66,176],"methods,":[67],"particular,":[69],"artificial":[70],"neural":[71],"networks,":[72],"order":[74],"to":[75,82,96,119,178],"classify":[76],"motion":[79,103,131,181],"state":[80,112,182],"predict":[83],"future":[85],"trajectory":[86,196],"VRUs.":[89],"Both":[90],"model":[91,191],"types":[92],"also":[94,200],"combined":[95],"enable":[97],"application":[99],"specifically":[101],"trained":[102],"predictors":[104],"continuously":[108],"updated":[109],"pseudo":[110],"probabilistic":[111],"classification.":[113,132],"Furthermore,":[114],"architecture":[116],"used":[118,153],"evaluate":[120],"motion-specific":[121],"physical":[122],"for":[124,154,203],"starting":[125,211],"stopping":[127,213],"video-based":[129],"pedestrian":[130,142],"A":[133],"comprehensive":[134],"dataset":[135],"consisting":[136],"total":[139],"1068":[141],"494":[144],"cyclist":[145],"acquired":[147],"at":[148],"an":[149],"urban":[150],"intersection":[151],"optimization,":[155],"training,":[156],"evaluation":[158],"different":[161],"models.":[162],"The":[163,195],"results":[164],"show":[165],"substantially":[166],"higher":[167],"classification":[168],"rates":[169],"ability,":[172],"through":[173],"approaches,":[177],"earlier":[179],"recognize":[180],"changes":[183],"than":[184],"way":[187],"interacting":[189],"multiple":[190],"(IMM)":[192],"Kalman":[193],"filtering.":[194],"prediction":[197],"quality":[198],"has":[199],"been":[201],"improved":[202],"all":[204],"kinds":[205],"test":[207],"scenes,":[208],"especially":[209],"when":[210],"motions":[214],"included.":[216],"Here,":[217],"37%":[218],"41%":[220],"fewer":[221],"position":[222],"errors":[223],"were":[224],"achieved":[225],"average,":[227],"respectively.":[228]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}
