{"id":"https://openalex.org/W7155200753","doi":"https://doi.org/10.1007/s10994-026-07036-8","title":"SCI-IDEA: Context-Aware Scientific Ideation Using Token and Sentence Embeddings","display_name":"SCI-IDEA: Context-Aware Scientific Ideation Using Token and Sentence Embeddings","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155200753","doi":"https://doi.org/10.1007/s10994-026-07036-8"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-026-07036-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-026-07036-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-026-07036-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"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","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-026-07036-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116609038","display_name":"Farhana Keya","orcid":"https://orcid.org/0000-0002-3782-8069"},"institutions":[{"id":"https://openalex.org/I2802635041","display_name":"Technische Informationsbibliothek (TIB)","ror":"https://ror.org/04aj4c181","country_code":"DE","type":"archive","lineage":["https://openalex.org/I2802635041","https://openalex.org/I315704651"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Farhana Keya","raw_affiliation_strings":["TIB\u2212Leibniz Information Centre for Science and Technology, Hannover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TIB\u2212Leibniz Information Centre for Science and Technology, Hannover, Germany","institution_ids":["https://openalex.org/I2802635041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028535577","display_name":"Gollam Rabby","orcid":"https://orcid.org/0000-0002-1212-0101"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]},{"id":"https://openalex.org/I4210136150","display_name":"L3S Research Center","ror":"https://ror.org/039t4wk02","country_code":"DE","type":"facility","lineage":["https://openalex.org/I114112103","https://openalex.org/I4210136150","https://openalex.org/I94509681"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Gollam Rabby","raw_affiliation_strings":["L3S Research Center, Leibniz University Hannover, Hannover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L3S Research Center, Leibniz University Hannover, Hannover, Germany","institution_ids":["https://openalex.org/I4210136150","https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134249077","display_name":"S\u00f6ren Auer","orcid":null},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]},{"id":"https://openalex.org/I2802635041","display_name":"Technische Informationsbibliothek (TIB)","ror":"https://ror.org/04aj4c181","country_code":"DE","type":"archive","lineage":["https://openalex.org/I2802635041","https://openalex.org/I315704651"]},{"id":"https://openalex.org/I4210136150","display_name":"L3S Research Center","ror":"https://ror.org/039t4wk02","country_code":"DE","type":"facility","lineage":["https://openalex.org/I114112103","https://openalex.org/I4210136150","https://openalex.org/I94509681"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"S\u00f6ren Auer","raw_affiliation_strings":["L3S Research Center, Leibniz University Hannover, Hannover, Germany","TIB\u2212Leibniz Information Centre for Science and Technology, Hannover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L3S Research Center, Leibniz University Hannover, Hannover, Germany","institution_ids":["https://openalex.org/I4210136150","https://openalex.org/I114112103"]},{"raw_affiliation_string":"TIB\u2212Leibniz Information Centre for Science and Technology, Hannover, Germany","institution_ids":["https://openalex.org/I2802635041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102785999","display_name":"Sahar Vahdati","orcid":"https://orcid.org/0000-0002-7171-169X"},"institutions":[{"id":"https://openalex.org/I2802635041","display_name":"Technische Informationsbibliothek (TIB)","ror":"https://ror.org/04aj4c181","country_code":"DE","type":"archive","lineage":["https://openalex.org/I2802635041","https://openalex.org/I315704651"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sahar Vahdati","raw_affiliation_strings":["TIB\u2212Leibniz Information Centre for Science and Technology, Hannover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TIB\u2212Leibniz Information Centre for Science and Technology, Hannover, Germany","institution_ids":["https://openalex.org/I2802635041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009542542","display_name":"Prasenjit Mitra","orcid":"https://orcid.org/0000-0002-7530-9497"},"institutions":[{"id":"https://openalex.org/I4210130200","display_name":"Carnegie Mellon University Africa","ror":"https://ror.org/02f33m021","country_code":"RW","type":"education","lineage":["https://openalex.org/I4210130200","https://openalex.org/I74973139"]}],"countries":["RW"],"is_corresponding":false,"raw_author_name":"Prasenjit Mitra","raw_affiliation_strings":["Carnegie Mellon University Africa, Kigali, Rwanda"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University Africa, Kigali, Rwanda","institution_ids":["https://openalex.org/I4210130200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078133624","display_name":"Mohamad Yaser Jaradeh","orcid":"https://orcid.org/0000-0001-8777-2780"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]},{"id":"https://openalex.org/I4210136150","display_name":"L3S Research Center","ror":"https://ror.org/039t4wk02","country_code":"DE","type":"facility","lineage":["https://openalex.org/I114112103","https://openalex.org/I4210136150","https://openalex.org/I94509681"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mohamad Yaser Jaradeh","raw_affiliation_strings":["L3S Research Center, Leibniz University Hannover, Hannover, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"L3S Research Center, Leibniz University Hannover, Hannover, Germany","institution_ids":["https://openalex.org/I4210136150","https://openalex.org/I114112103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028535577"],"corresponding_institution_ids":["https://openalex.org/I114112103","https://openalex.org/I4210136150"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42447703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"115","issue":"5","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.27090001106262207,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.27090001106262207,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.21040000021457672,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.06440000236034393,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.7368999719619751},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.630299985408783},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5008999705314636},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.44850000739097595},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.44440001249313354},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.42149999737739563},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4165000021457672},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4115999937057495}],"concepts":[{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.7368999719619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6771000027656555},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.630299985408783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5748000144958496},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5008999705314636},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4957999885082245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47530001401901245},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.44850000739097595},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.3190000057220459},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.29820001125335693},{"id":"https://openalex.org/C2779346075","wikidata":"https://www.wikidata.org/wiki/Q7268763","display_name":"Quality Score","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2750000059604645},{"id":"https://openalex.org/C62897895","wikidata":"https://www.wikidata.org/wiki/Q1915482","display_name":"Mean opinion score","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C2779267917","wikidata":"https://www.wikidata.org/wiki/Q170028","display_name":"Deception","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C170477896","wikidata":"https://www.wikidata.org/wiki/Q17039022","display_name":"Ideation","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10994-026-07036-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-026-07036-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-026-07036-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"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","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10994-026-07036-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-026-07036-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-026-07036-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"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","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4864138662815094,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322379","display_name":"Gottfried Wilhelm Leibniz Universit\u00e4t Hannover","ror":"https://ror.org/0304hq317"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7155200753.pdf","grobid_xml":"https://content.openalex.org/works/W7155200753.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2781247022","https://openalex.org/W3204302424","https://openalex.org/W4283588026","https://openalex.org/W4327810158","https://openalex.org/W4391670409","https://openalex.org/W4402952666","https://openalex.org/W4403780163","https://openalex.org/W4403784034","https://openalex.org/W4405627820","https://openalex.org/W4405903187","https://openalex.org/W4406741148","https://openalex.org/W4406779522","https://openalex.org/W4407207247","https://openalex.org/W4411120082","https://openalex.org/W4412875478","https://openalex.org/W4412887852","https://openalex.org/W4416043407","https://openalex.org/W4416260836","https://openalex.org/W6910537132","https://openalex.org/W7124278255"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Generating":[1],"context-aware,":[2],"high-quality,":[3],"and":[4,46,89,106,125,139,228,263],"innovative":[5],"scientific":[6],"ideas":[7,94],"remains":[8],"a":[9,19,28,82,130,140,163,204,210],"central":[10],"challenge":[11],"in":[12,284],"AI-supported":[13],"research.":[14],"We":[15,108],"introduce":[16],"SCI-IDEA":[17,110,199],",":[18],"two-stage":[20],"framework":[21],"combining":[22],"large":[23],"language":[24],"models":[25],"(LLMs)":[26],"with":[27,81,137,143,166,200,276],"specialised":[29],"Aha-Moment":[30],"Detection":[31],"module":[32],"for":[33,103],"iterative":[34],"idea":[35,193],"refinement.":[36],"The":[37,75],"first":[38],"stage":[39,77],"extracts":[40],"structured":[41],"facets:":[42],"objectives,":[43],"methodology,":[44],"evaluation,":[45],"future":[47],"work":[48,281],"from":[49],"previous":[50],"publications,":[51],"compressing":[52],"each":[53],"paper":[54],"to":[55,60,86,292],"$${\\sim":[56],"}$$":[57],"200":[58],"tokens":[59],"enable":[61],"scalable":[62],"processing":[63],"of":[64,133,191,208,259],"researcher":[65,114],"profiles":[66],"that":[67,180],"would":[68],"otherwise":[69],"exceed":[70,156],"frontier":[71],"LLM":[72],"context":[73,90,261],"windows.":[74],"second":[76],"integrates":[78],"these":[79],"facets":[80],"token-level":[83,201,264],"embedding":[84,123],"approach":[85],"identify":[87],"novelty":[88,105,265],"gaps,":[91],"indicating":[92,179],"candidate":[93],"as":[95],"Aha":[96],"moments":[97],"when":[98],"they":[99],"surpass":[100],"predefined":[101],"thresholds":[102],"both":[104],"surprise.":[107],"evaluate":[109],"across":[111],"100":[112],"computer-science":[113],"profiles,":[115],"4":[116],"LLMs":[117],"(GPT-4o,":[118],"GPT\u22124.5,":[119],"DeepSeek-32B,":[120],"DeepSeek-70B),":[121],"three":[122],"strategies,":[124],"5":[126],"prompting":[127],"configurations":[128],"via":[129],"hybrid":[131],"protocol":[132],"automated":[134,181],"LLM-as-judge":[135],"scoring":[136],"GPT\u22124.1":[138],"human":[141],"evaluation":[142,150],"15":[144],"PhD-level":[145],"domain":[146,278],"experts.":[147,279],"These":[148,253],"two":[149],"signals":[151],"diverge":[152],"substantially:":[153],"LLM-based":[154],"scores":[155,182,234],"expert":[157],"ratings":[158],"by":[159,231],"3\u20134":[160],"points":[161],"on":[162],"10-point":[164],"scale,":[165],"near-zero":[167],"inter-rater":[168],"correlation":[169],"(":[170,219,235],"$$r":[171],"=":[172,221],"0.02$$":[173],"\u20130.17,":[174],"$$p":[175,224,238],"&gt;":[176],"0.05$$":[177,226],"),":[178],"reflect":[183],"relative":[184],"architectural":[185,257],"comparisons":[186],"rather":[187],"than":[188],"human-verified":[189],"measures":[190],"absolute":[192,251],"quality.":[194],"Within":[195],"the":[196,216,285],"LLM-evaluated":[197],"setting,":[198],"embeddings":[202],"achieves":[203],"mean":[205],"quality":[206],"score":[207],"6.97,":[209],"modest":[211],"but":[212,289],"constant":[213],"improvement":[214],"over":[215],"LLM-only":[217],"baseline":[218],"$$\\Delta":[220],"+0.20$$":[222],"points;":[223],"&lt;":[225,239],")":[227],"driven":[229],"primarily":[230],"improved":[232],"feasibility":[233],"$$+0.21$$":[236],"points,":[237],"0.001$$":[240],").":[241],"Expert":[242],"evaluators":[243],"independently":[244],"confirmed":[245],"this":[246],"trend":[247],"while":[248],"assigning":[249],"lower":[250],"scores.":[252],"findings":[254],"suggest":[255],"an":[256],"advantage":[258],"facet-based":[260],"modelling":[262],"detection,":[266],"though":[267],"their":[268],"practical":[269],"importance":[270],"deserves":[271],"validation":[272],"through":[273],"longitudinal":[274],"studies":[275],"larger":[277],"This":[280],"is":[282],"validated":[283],"computer":[286],"science":[287],"domain,":[288],"its":[290],"application":[291],"other":[293],"fields":[294],"requires":[295],"further":[296],"investigation.":[297]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-04-23T00:00:00"}
