{"id":"https://openalex.org/W1914749446","doi":"https://doi.org/10.1109/cibcb.2015.7300292","title":"Stress and productivity performance in the workforce modelled with binary decision automata","display_name":"Stress and productivity performance in the workforce modelled with binary decision automata","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W1914749446","doi":"https://doi.org/10.1109/cibcb.2015.7300292","mag":"1914749446"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb.2015.7300292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb.2015.7300292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111677808","display_name":"Matthew Page","orcid":null},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Matthew Page","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada","Department of Mathematics and Statistics at the University of Guelph in Guelph, Ontario, CANADA, N1G 2W1"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"Department of Mathematics and Statistics at the University of Guelph in Guelph, Ontario, CANADA, N1G 2W1","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080870632","display_name":"Daniel Ashlock","orcid":"https://orcid.org/0000-0003-2209-7504"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Daniel Ashlock","raw_affiliation_strings":["Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada","Department of Mathematics and Statistics at the University of Guelph in Guelph, Ontario, CANADA, N1G 2W1"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"Department of Mathematics and Statistics at the University of Guelph in Guelph, Ontario, CANADA, N1G 2W1","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111677808"],"corresponding_institution_ids":["https://openalex.org/I79817857"],"apc_list":null,"apc_paid":null,"fwci":0.9185,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77730527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10410","display_name":"COVID-19 epidemiological studies","score":0.9761000275611877,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"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/T11810","display_name":"Complex Systems and Decision Making","score":0.9046000242233276,"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/representation","display_name":"Representation (politics)","score":0.5997060537338257},{"id":"https://openalex.org/keywords/automaton","display_name":"Automaton","score":0.5696242451667786},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.5635247826576233},{"id":"https://openalex.org/keywords/productivity","display_name":"Productivity","score":0.5387675762176514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5363133549690247},{"id":"https://openalex.org/keywords/agent-based-model","display_name":"Agent-based model","score":0.4934047758579254},{"id":"https://openalex.org/keywords/workforce","display_name":"Workforce","score":0.48881790041923523},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.4632500410079956},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.46082034707069397},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4580253064632416},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4336954653263092},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.43138206005096436},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3860948085784912},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.340478777885437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3197348713874817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23833131790161133},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.22473910450935364},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.18280601501464844},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16103285551071167},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.14611664414405823},{"id":"https://openalex.org/keywords/demography","display_name":"Demography","score":0.10044881701469421},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.09332767128944397}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5997060537338257},{"id":"https://openalex.org/C112505250","wikidata":"https://www.wikidata.org/wiki/Q787116","display_name":"Automaton","level":2,"score":0.5696242451667786},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.5635247826576233},{"id":"https://openalex.org/C204983608","wikidata":"https://www.wikidata.org/wiki/Q2111958","display_name":"Productivity","level":2,"score":0.5387675762176514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5363133549690247},{"id":"https://openalex.org/C2780873155","wikidata":"https://www.wikidata.org/wiki/Q392811","display_name":"Agent-based model","level":2,"score":0.4934047758579254},{"id":"https://openalex.org/C2778139618","wikidata":"https://www.wikidata.org/wiki/Q13440398","display_name":"Workforce","level":2,"score":0.48881790041923523},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.4632500410079956},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.46082034707069397},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4580253064632416},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4336954653263092},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.43138206005096436},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3860948085784912},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.340478777885437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3197348713874817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23833131790161133},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.22473910450935364},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.18280601501464844},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16103285551071167},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14611664414405823},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.10044881701469421},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.09332767128944397},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb.2015.7300292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb.2015.7300292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5400000214576721,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W129505615","https://openalex.org/W323040450","https://openalex.org/W1508148070","https://openalex.org/W1526546163","https://openalex.org/W1527532375","https://openalex.org/W1569757501","https://openalex.org/W1970948703","https://openalex.org/W1974975426","https://openalex.org/W1986687458","https://openalex.org/W1987375729","https://openalex.org/W2007337496","https://openalex.org/W2012588232","https://openalex.org/W2014217338","https://openalex.org/W2022947365","https://openalex.org/W2052232389","https://openalex.org/W2056102643","https://openalex.org/W2057333812","https://openalex.org/W2062389185","https://openalex.org/W2121418733","https://openalex.org/W2122356930","https://openalex.org/W2129786343","https://openalex.org/W2142318603","https://openalex.org/W2147558499","https://openalex.org/W2492926234","https://openalex.org/W4238753141","https://openalex.org/W6605287417","https://openalex.org/W6631400761"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2383111961"],"abstract_inverted_index":{"This":[0,47,170],"study":[1,106,171],"is":[2,110,120,126],"the":[3,15,19,59,96,113,123,166,174],"third":[4],"in":[5,90,101,140,177],"a":[6,29,54,84,107,178,186],"series":[7,36],"developing":[8],"an":[9,91],"agent":[10,114],"based":[11],"ecological":[12],"model":[13,48,57,69,175],"of":[14,21,37,41,58,95,143,145,151],"workplace":[16],"focused":[17],"on":[18,50,66,112],"impact":[20],"stress.":[22],"Stress":[23],"and":[24,149,153,184],"stress-related":[25],"health":[26],"problems":[27],"are":[28,159],"serious":[30],"matter":[31],"but,":[32],"prior":[33],"to":[34,131,164],"this":[35,105],"studies,":[38],"quantitative":[39],"modeling":[40],"stress":[42,60],"has":[43],"been":[44],"substantially":[45],"neglected.":[46],"builds":[49],"earlier":[51,102],"work,":[52],"incorporating":[53],"more":[55],"realistic":[56],"relief":[61],"caused":[62],"by":[63],"time":[64],"off":[65],"weekends.":[67],"The":[68],"also":[70],"examines":[71],"drug":[72,155],"use":[73],"as":[74,98],"something":[75],"that":[76,122,173],"can":[77],"be":[78],"learned":[79,82,152],"spontaneously":[80],"or":[81],"from":[83],"mentor":[85],"rather":[86],"than":[87],"being":[88],"present":[89],"endemic,":[92],"fixed":[93],"fraction":[94],"population,":[97],"it":[99],"was":[100],"studies.":[103],"In":[104],"parameter":[108,132],"exploration":[109],"performed":[111],"representation,":[115],"binary":[116],"decision":[117],"automata.":[118],"It":[119],"found":[121],"BDA":[124],"representation":[125],"highly":[127],"adaptive,":[128],"responding":[129],"robustly":[130],"changes.":[133],"Parameters":[134],"investigated":[135],"include":[136],"number":[137],"internal":[138],"states":[139],"agents,":[141],"accuracy":[142],"imitation":[144],"mentors,":[146],"work":[147],"requirements,":[148],"probabilities":[150],"spontaneous":[154],"use.":[156],"Parameter":[157],"values":[158],"taken":[160],"beyond":[161],"reasonable":[162,179],"ranges":[163],"examine":[165],"model's":[167],"failure":[168],"modes.":[169],"demonstrates":[172],"behaves":[176],"fashion,":[180],"determines":[181],"its":[182],"limits,":[183],"established":[185],"baseline":[187],"for":[188],"further":[189],"investigation.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}