{"id":"https://openalex.org/W7126531176","doi":null,"title":"AI Transcription of Historical Oology Cards: A Proof of Concept Using a Multimodal Large Language Model","display_name":"AI Transcription of Historical Oology Cards: A Proof of Concept Using a Multimodal Large Language Model","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7126531176"},"language":"en","primary_location":{"id":"pmh:oai:ecommons.cornell.edu:1813/118249","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/1813/118249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400757","display_name":"eCommons (Cornell University)","issn_l":null,"issn":null,"is_oa":false,"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":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation or thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/1813/118249","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124615164","display_name":"Grete Pasch-Vald?s","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pasch-Vald?s, Grete","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5124615164"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12377","display_name":"Digital Humanities and Scholarship","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.0012000000569969416,"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/multimodal-large-language-models","display_name":"multimodal large language models","score":0.8930000066757202},{"id":"https://openalex.org/keywords/gpt-4o","display_name":"GPT-4o","score":0.9779999852180481},{"id":"https://openalex.org/keywords/natural-history-specimens","display_name":"natural history specimens","score":0.6539999842643738},{"id":"https://openalex.org/keywords/prompting-strategies","display_name":"prompting strategies","score":0.6729999780654907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7432000041007996},{"id":"https://openalex.org/C2779308522","wikidata":"https://www.wikidata.org/wiki/Q843958","display_name":"Digitization","level":2,"score":0.7297999858856201},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6855000257492065},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.6712999939918518},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5735999941825867},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5489000082015991},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.47609999775886536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4641999900341034},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C2779547435","wikidata":"https://www.wikidata.org/wiki/Q1121492","display_name":"Directive","level":2,"score":0.4327000081539154},{"id":"https://openalex.org/C67277372","wikidata":"https://www.wikidata.org/wiki/Q7449085","display_name":"Semantic role labeling","level":3,"score":0.36410000920295715},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32359999418258667},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.3181999921798706},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3174000084400177},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C45874996","wikidata":"https://www.wikidata.org/wiki/Q37045","display_name":"Markup language","level":3,"score":0.2856000065803528},{"id":"https://openalex.org/C124978682","wikidata":"https://www.wikidata.org/wiki/Q1201019","display_name":"Proof of concept","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C2993724205","wikidata":"https://www.wikidata.org/wiki/Q315","display_name":"Human language","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ecommons.cornell.edu:1813/118249","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/1813/118249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400757","display_name":"eCommons (Cornell University)","issn_l":null,"issn":null,"is_oa":false,"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":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation or thesis"}],"best_oa_location":{"id":"pmh:oai:ecommons.cornell.edu:1813/118249","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/1813/118249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400757","display_name":"eCommons (Cornell University)","issn_l":null,"issn":null,"is_oa":false,"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":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation or thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4410761886","https://openalex.org/W4417226674","https://openalex.org/W4408533932","https://openalex.org/W7221541577","https://openalex.org/W4404347965","https://openalex.org/W4406735876","https://openalex.org/W7135203448","https://openalex.org/W7222975016","https://openalex.org/W6885138107","https://openalex.org/W7108094025"],"abstract_inverted_index":{"In":[0],"natural":[1],"history":[2],"museums,":[3],"handwritten":[4,110],"specimen":[5],"data":[6,91],"cards":[7,60,113,150],"serve":[8],"as":[9,166],"repositories":[10],"of":[11,40,47,57,72,108,134,140],"field":[12],"note-derived":[13],"biological":[14],"information.":[15],"Digitizing":[16],"these":[17],"records":[18],"is":[19],"essential":[20],"to":[21,37,53,153],"preserve":[22],"their":[23],"content":[24],"and":[25,88,101,111,123],"facilitate":[26],"worldwide":[27],"research":[28],"access.":[29],"However,":[30],"this":[31],"process":[32],"remains":[33],"a":[34,96,102,141,170],"bottleneck":[35],"due":[36],"the":[38,45,55,62,68,116,135,138,149],"complexities":[39],"historical":[41,58,180],"handwriting.":[42],"I":[43],"evaluate":[44],"potential":[46],"Multimodal":[48],"Large":[49],"Language":[50],"Models":[51],"(MLLMs)":[52],"automate":[54],"transcription":[56],"oology":[59],"from":[61,145],"Robert":[63],"B.":[64],"Lyle":[65],"Collection":[66],"at":[67],"Cornell":[69],"University":[70],"Museum":[71],"Vertebrates.":[73],"Moving":[74],"beyond":[75],"traditional":[76],"Optical":[77],"Character":[78],"Recognition":[79],"(OCR)":[80],"pipelines,":[81],"experimentation":[82],"tested":[83],"whether":[84],"GPT-4o":[85],"could":[86],"transcribe":[87],"interpret":[89],"card":[90],"using":[92],"two":[93],"prompting":[94],"strategies:":[95],"literal":[97],"\"strict":[98],"transcription\"":[99],"directive":[100,118],"structured":[103,117],"\"thinking":[104],"archivist\"":[105],"directive.":[106],"Analysis":[107],"262":[109],"typed":[112],"reveals":[114],"that":[115,159,174],"significantly":[119],"improved":[120],"semantic":[121],"accuracy":[122],"reduced":[124],"median":[125],"human":[126,176],"review":[127],"time,":[128],"yielding":[129],"error-free":[130],"transcripts":[131],"for":[132,178],"74%":[133],"dataset.":[136],"Furthermore,":[137],"development":[139],"\"Hesitation":[142],"Score\"":[143],"derived":[144],"token-level":[146],"log-probabilities":[147],"identified":[148],"most":[151],"likely":[152],"contain":[154],"errors.":[155],"These":[156],"results":[157],"demonstrate":[158],"MLLMs":[160],"can":[161],"accelerate":[162],"digitization":[163],"by":[164],"acting":[165],"intelligent":[167],"transcribers,":[168],"enabling":[169],"scalable,":[171],"triage-based":[172],"workflow":[173],"optimizes":[175],"effort":[177],"large-scale":[179],"transcription.":[181]},"counts_by_year":[],"updated_date":"2026-09-11T09:22:31.653822","created_date":"2026-02-02T00:00:00"}