{"id":"https://openalex.org/W4385755683","doi":"https://doi.org/10.1088/2632-2153/acefab","title":"Improving materials property predictions for graph neural networks with minimal feature engineering <sup>*</sup>","display_name":"Improving materials property predictions for graph neural networks with minimal feature engineering <sup>*</sup>","publication_year":2023,"publication_date":"2023-08-11","ids":{"openalex":"https://openalex.org/W4385755683","doi":"https://doi.org/10.1088/2632-2153/acefab"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/acefab","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acefab","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acefab/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acefab/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089801879","display_name":"Guojing Cong","orcid":"https://orcid.org/0000-0003-0850-7714"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Guojing Cong","raw_affiliation_strings":["Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, Tennessee, 37831-2008, UNITED STATES"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, Tennessee, 37831-2008, UNITED STATES","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085597140","display_name":"Victor Fung","orcid":"https://orcid.org/0000-0002-3347-6983"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor Fung","raw_affiliation_strings":["Georgia Institute of Technology, Georgia Institute of Technology, Atlanta, Georgia, 30332-0002, UNITED STATES"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Georgia Institute of Technology, Atlanta, Georgia, 30332-0002, UNITED STATES","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089801879"],"corresponding_institution_ids":["https://openalex.org/I1289243028"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":0.4721,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.55157296,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"4","issue":"3","first_page":"035030","last_page":"035030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9775000214576721,"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/feature-engineering","display_name":"Feature engineering","score":0.8038617372512817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193576097488403},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5877783298492432},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5785665512084961},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5436779856681824},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5262438654899597},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5064979791641235},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48659002780914307},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47690606117248535},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45841026306152344},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44162362813949585},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4216502010822296},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.35337764024734497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3400786519050598},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.256635457277298},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12098127603530884}],"concepts":[{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.8038617372512817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193576097488403},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5877783298492432},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5785665512084961},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5436779856681824},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5262438654899597},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5064979791641235},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48659002780914307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47690606117248535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45841026306152344},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44162362813949585},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4216502010822296},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35337764024734497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3400786519050598},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.256635457277298},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12098127603530884},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1088/2632-2153/acefab","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acefab","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acefab/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:osti.gov:2000267","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2000267","pdf_url":"https://www.osti.gov/servlets/purl/2000267","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"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":null},{"id":"pmh:oai:doaj.org/article:b5b30a43773b4d108d973dace1cb65a4","is_oa":true,"landing_page_url":"https://doaj.org/article/b5b30a43773b4d108d973dace1cb65a4","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 4, Iss 3, p 035030 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/acefab","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/acefab","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/acefab/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1489425746","display_name":null,"funder_award_id":"DE-AC05-00OR22725","funder_id":"https://openalex.org/F4320332359","funder_display_name":"Office of Science"},{"id":"https://openalex.org/G1645119126","display_name":null,"funder_award_id":"AC05-00OR22725","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G2042897603","display_name":null,"funder_award_id":"DE-AC05-00OR2272","funder_id":"https://openalex.org/F4320316892","funder_display_name":"UT-Battelle"},{"id":"https://openalex.org/G2296932962","display_name":null,"funder_award_id":"DE-AC05-00OR227","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G3299391273","display_name":null,"funder_award_id":"E-AC05-00OR22725","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G4423657506","display_name":null,"funder_award_id":"AC05-00OR22725","funder_id":"https://openalex.org/F4320338287","funder_display_name":"Oak Ridge National Laboratory"},{"id":"https://openalex.org/G4694431782","display_name":null,"funder_award_id":"DE-AC05-00OR2272","funder_id":"https://openalex.org/F4320332359","funder_display_name":"Office of Science"},{"id":"https://openalex.org/G5726405315","display_name":null,"funder_award_id":"DE-AC05","funder_id":"https://openalex.org/F4320306250","funder_display_name":"Battelle"},{"id":"https://openalex.org/G6129992089","display_name":null,"funder_award_id":"DE-AC05-","funder_id":"https://openalex.org/F4320316892","funder_display_name":"UT-Battelle"},{"id":"https://openalex.org/G6488227018","display_name":null,"funder_award_id":"DE-AC05-00OR227","funder_id":"https://openalex.org/F4320332359","funder_display_name":"Office of Science"},{"id":"https://openalex.org/G6864165199","display_name":null,"funder_award_id":"DE-AC05-00OR22725","funder_id":"https://openalex.org/F4320306250","funder_display_name":"Battelle"},{"id":"https://openalex.org/G691578896","display_name":null,"funder_award_id":"DE-AC05-00OR2272","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G7114708214","display_name":null,"funder_award_id":"DE-AC05-00OR2272","funder_id":"https://openalex.org/F4320338287","funder_display_name":"Oak Ridge National Laboratory"},{"id":"https://openalex.org/G7995982022","display_name":null,"funder_award_id":"DE-AC05","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8269158468","display_name":null,"funder_award_id":"AC05-00OR22725","funder_id":"https://openalex.org/F4320332359","funder_display_name":"Office of Science"},{"id":"https://openalex.org/G8414908677","display_name":null,"funder_award_id":"DE-AC0","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8799952057","display_name":null,"funder_award_id":"DE-AC05-00OR22","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8813984943","display_name":null,"funder_award_id":"DE-AC05-00OR22725","funder_id":"https://openalex.org/F4320316892","funder_display_name":"UT-Battelle"},{"id":"https://openalex.org/G8906985441","display_name":null,"funder_award_id":"00OR22725","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8943143067","display_name":null,"funder_award_id":"AC05-00OR22725","funder_id":"https://openalex.org/F4320316892","funder_display_name":"UT-Battelle"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320306250","display_name":"Battelle","ror":"https://ror.org/01h5tnr73"},{"id":"https://openalex.org/F4320316892","display_name":"UT-Battelle","ror":"https://ror.org/04nza6677"},{"id":"https://openalex.org/F4320332359","display_name":"Office of Science","ror":"https://ror.org/00mmn6b08"},{"id":"https://openalex.org/F4320337506","display_name":"Advanced Scientific Computing Research","ror":"https://ror.org/0012c7r22"},{"id":"https://openalex.org/F4320338287","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385755683.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1902312384","https://openalex.org/W1992985800","https://openalex.org/W2004885493","https://openalex.org/W2194775991","https://openalex.org/W2304767338","https://openalex.org/W2524052714","https://openalex.org/W2527189750","https://openalex.org/W2726670313","https://openalex.org/W2766856748","https://openalex.org/W2788775653","https://openalex.org/W2923693308","https://openalex.org/W2949095042","https://openalex.org/W2950890616","https://openalex.org/W2964015378","https://openalex.org/W2978508283","https://openalex.org/W2983028326","https://openalex.org/W3000754666","https://openalex.org/W3013896483","https://openalex.org/W3015912868","https://openalex.org/W3048908832","https://openalex.org/W3049517558","https://openalex.org/W3098062507","https://openalex.org/W3101379108","https://openalex.org/W3102096994","https://openalex.org/W3103227378","https://openalex.org/W3126046487","https://openalex.org/W3198599144","https://openalex.org/W3212512279","https://openalex.org/W4283641078","https://openalex.org/W4287828570","https://openalex.org/W4297412336","https://openalex.org/W4297733535","https://openalex.org/W4300537282","https://openalex.org/W4319779247","https://openalex.org/W4385245566","https://openalex.org/W6687483927","https://openalex.org/W6726873649","https://openalex.org/W6727189038","https://openalex.org/W6739901393","https://openalex.org/W6745537798","https://openalex.org/W6749031613","https://openalex.org/W6768314895","https://openalex.org/W6771809849","https://openalex.org/W6839042332","https://openalex.org/W6843715226","https://openalex.org/W6849320840"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4387478977","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W3034267371"],"abstract_inverted_index":{"Abstract":[0],"Graph":[1],"neural":[2,52],"networks":[3],"(GNNs)":[4],"have":[5,18],"been":[6],"employed":[7],"in":[8,22,190],"materials":[9],"research":[10],"to":[11,49,169],"predict":[12],"physical":[13],"and":[14,17,46,84,88,97,144,185],"functional":[15],"properties,":[16],"achieved":[19],"superior":[20],"performance":[21,133,155],"several":[23],"application":[24],"domains":[25],"over":[26],"prior":[27],"machine":[28],"learning":[29],"approaches.":[30],"Recent":[31],"studies":[32],"incorporate":[33],"features":[34,60,80,120,140,168],"of":[35],"increasing":[36],"complexity":[37],"such":[38],"as":[39,95,101,116],"Gaussian":[40],"radial":[41],"functions,":[42,45],"plane":[43],"wave":[44],"angular":[47],"terms":[48],"augment":[50],"the":[51,56,106,157,179],"network":[53],"models,":[54],"with":[55,93,135,138,148],"expectation":[57],"that":[58,73,126],"these":[59],"are":[61,121],"critical":[62],"for":[63,112,141,181],"achieving":[64],"a":[65,71,104,124],"high":[66],"performance.":[67],"Here,":[68],"we":[69,131,151],"propose":[70],"GNN":[72],"adopts":[74],"edge":[75,79],"convolution":[76],"where":[77],"hidden":[78],"evolve":[81],"during":[82],"training":[83],"extensive":[85],"attention":[86],"mechanisms,":[87],"operates":[89],"on":[90],"simple":[91],"graphs":[92],"atoms":[94],"nodes":[96],"distances":[98],"between":[99],"them":[100],"edges.":[102],"As":[103],"result,":[105],"same":[107],"model":[108,125],"can":[109],"be":[110],"used":[111],"very":[113],"different":[114],"tasks":[115],"no":[117,128],"other":[118],"domain-specific":[119,163],"used.":[122],"With":[123],"uses":[127],"feature":[129,183],"engineering,":[130],"achieve":[132,152,170],"comparable":[134],"state-of-the-art":[136,171],"models":[137],"elaborate":[139,182],"formation":[142],"energy":[143],"band":[145],"gap":[146],"prediction":[147],"standard":[149],"benchmarks;":[150],"even":[153],"better":[154],"when":[156],"dataset":[158],"size":[159],"increases.":[160],"Although":[161],"some":[162],"datasets":[164],"still":[165,186],"require":[166],"hand-crafted":[167],"results,":[172],"our":[173],"selected":[174],"architecture":[175],"choices":[176],"greatly":[177],"reduce":[178],"need":[180],"engineering":[184],"maintain":[187],"predictive":[188],"power":[189],"comparison.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2023-08-12T00:00:00"}