Bibliography

This is an automatically generated bibliography describing the content of this study carrel.

1. anderson-responsible-2024
   • author: anderson
   • title: anderson-responsible-2024
   • date: 2024
   • words: 6088
   • flesch: 49
   • summary: In the case of television news, for example, chapterization would divide the shows into news segments. A graph would show linkages between news segments and news shows, allowing users to traverse segments based on their nearness or distance to events rather than on keywords.
   • keywords: 2022; abstracts; access; accuracy; amazon; analysis; anderson; archive; asr; available; aws; backlog; captions; case; collection; commercial; computational; data; database; different; duran; e805; embeddings; entities; escience; escience librarianship; ethical; example; future; goal; https://doi.org/10.7191/jeslib.805; information; intelligence; journal; key; labor; lake; language; learning; librarianship; like; machine; media; metadata; model; names; need; news; ngrams; process; project; related; researchers; segments; services; spelling; staff; study; summarization; television; television news; terms; text; time; title; tools; transcripts; university; use; users; vanderbilt; video; vtna; web; words; workflow
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2. beltran-open-2024
   • author: beltran
   • title: beltran-open-2024
   • date: 2024
   • words: 5048
   • flesch: 33
   • summary: The proposal of a recommendation system derived from the idea to create a predictive model that would shed light on usage patterns of open science services. Along with these associates, Lauren Herckis, an anthropologist and affiliate of the Libraries, Simon Initiative, and the Human Computer Interaction Institute at CMU, has contributed in our efforts to identify collaborators and develop strategies to assess how users will engage with open science service and tool delivery in educational and research settings.
   • keywords: academic; access; analysis; approach; artificial; beltran; capstone; carnegie; case; challenges; chasz; cmu; community; computer; data; design; development; e804; educational; efforts; ethical; faculty; griego; herckis; https://doi.org/10.7191/jeslib.804; information; institutional; intelligence; journal; lauren; learning; lencia; librarianship; libraries; library; mellon; model; open; open science; practices; predictive; privacy; program; project; recommendation; recommendation system; research; resources; science; services; staff; strategies; students; study; support; system; team; tools; university; users; work
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3. elings-using-2024
   • author: elings
   • title: elings-using-2024
   • date: 2024
   • words: 5256
   • flesch: 38
   • summary: AI to transfer digital images securely via Box, with extracted data deposited in a private Github repository for further evaluation and editing by library staff. Overview This project offered our library the first opportunity to use AI/machine learning to improve data extraction from a digitized historical resource.
   • keywords: access; american; archival; archives; available; bancroft; berkeley; california; camp; cards; collections; community; complete; computational; confinement; content; data; dataset; densho; digital; digitized; doxie.ai; escience; ethical; extraction; february; file; forms; group; https://doi.org/10.7191/jeslib.850; images; incarcerated; individual; information; japanese; japanese american; journal; learning; librarianship; library; machine; machine learning; materials; meeting; members; national; number; original; pipeline; process; project; punch; records; research; resources; set; team; text; tools; transcription; use; war; work; wra-26; wwii
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4. feng-ethical-2024
   • author: feng
   • title: feng-ethical-2024
   • date: 2024
   • words: 7238
   • flesch: 31
   • summary: Such interactions can offer important guidance in constructing RCs and in considering ethical chatbot use more generally. In the “Disposition” set, librarians can contribute to ethical chatbot use by helping patrons to understand their relationship with chatbots, giving tips to students on how to raise awareness of their thinking and emotions, and to guide them towards a growth mindset during chatbot interactions.
   • keywords: academic; access; accuracy; acrl; association; bard; basic; capabilities; case; challenges; chatbot; chatgpt; chatgpt-4; code; considerations; consultations; critical; data; development; digital; divide; domain; e846; education; effective; escience; ethical; ethics; focus; framework; gpt; guidance; higher; https://doi.org/10.7191/jeslib.846; important; information; initial; instructors; interactions; issues; journal; knowledge; learning; librarians; librarianship; library; likely; literacy; new; output; patrons; perplexity; policies; products; project; prompts; quality; questioning; questions; related; relevant; research; responses; selected; set; sharegpt; simulation; social; students; study; subject; technology; terms; thinking; tools; topic; university; use; useful; users; work
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5. hosseini-ethical-2024
   • author: hosseini
   • title: hosseini-ethical-2024
   • date: 2024
   • words: 6559
   • flesch: 35
   • summary: Presently, this archive, which is the only historic genomics and Human Genome Project archive within NIH, houses an estimated two million pages that include cost-benefit analyses, interim reports, grantee presentations, internal memos, strategy papers, internal working documents, server logs, presentation, emails and scanned letters among senior personnel and toward external key stakeholders, and more—essentially anything that has been produced in relation to the institute’s core mission guiding and funding genomics. The NHGRI archive contains materials regarding conception, clearance, and approval of large projects inside a focused Institute.
   • keywords: access; amaral; analyses; archival; archive; artificial; challenges; computational; considerations; content; data; dataset; development; documents; donohue; e811; efforts; entity; escience; escience librarianship; ethical; fine; funding; future; genome; genome project; genomics; handwriting; handwritten; health; hgp; history; holmes; hosseini; https://doi.org/10.7191/jeslib.811; human; human genome; identification; individuals; information; initial; institute; institutions; intelligence; internal; international; involved; irb; journal; knowledge; kristi; language; large; learning; librarianship; library; llms; machine; materials; medicine; metadata; methods; models; mohammad; national; nhgri; nhgri archive; nih; northwestern; possible; privacy; private; program; project; research; review; risk; sciences; scientific; security; sequencing; standards; stoeger; studies; study; technical; text; thomas; tools; university; usa; use
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6. mannheimer-introduction-2024
   • author: mannheimer
   • title: mannheimer-introduction-2024
   • date: 2024
   • words: 2933
   • flesch: 28
   • summary: Accuracy can be influenced by AI systems themselves (such as sentiment analysis tools) or can be influenced by elements of AI systems (such as OCR and named entity recognition). Transparency A number of case study authors refer to transparency and explainability as core requirements for AI systems.
   • keywords: analysis; archives; beatles; bias; bozeman; case; considerations; data; divide; escience; et al; ethical; history; https://doi.org/10.7191/jeslib.860; issue; journal; librarianship; libraries; library; metadata; montana; new; open; privacy; project; recommendation; responsible; sentiment; services; special; state; studies; study; systems; tools; transparency; university; usa
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7. mcirvin-automatic-2024
   • author: mcirvin
   • title: mcirvin-automatic-2024
   • date: 2024
   • words: 4823
   • flesch: 40
   • summary: Top 25 Top 20 Top 15 Top 10 Top 5 Confirmed CS Score 0.6063 0.6145 0.6244 0.6329 0.6575 Overall CS Score 0.5688 0.5777 0.5901 0.6071 0.6370 Hit rate 14.2% 15.6% 17.8% 21.3% 27.5% Additional statistics on percentages of term cosine similarity scores - hit rate = % of generated descriptors that were confirmed. To operate the web application, users load in model-generated words, at which point, they can visually select a subset of descriptors to classify as confirmed descriptors.
   • keywords: accurate; additional; analysis; application; approach; artifacts; blacksburg; category; clothing; collections; column; core; cosine; costume; costume core; descriptors; digital; domain; dress; e845; efforts; embeddings; escience; expansion; experts; fashion; figure; format; google; historic; https://doi.org/10.7191/jeslib.845; human; initial; institute; journal; keywords; kirkland; librarianship; libraries; loop; metadata; metadata schema; mocha; model; new; news; nlp; online; overall; polytechnic; potential; process; processing; project; quality; results; schema; selections; set; similarity; students; terms; university; use; users; virginia; vocabulary; work
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8. pastva-implementation-2024
   • author: pastva
   • title: pastva-implementation-2024
   • date: 2024
   • words: 6683
   • flesch: 39
   • summary: AI tools have the potential to automate certain tasks, which could change the nature of liaison work and require new skills. Subject librarians can identify creative thinking and perform scaffolded instruction that compliments AI tools, and enhances their services rather than replace them.
   • keywords: academic; access; appendix; article; artificial; assessment; best; biases; carnegie; change; cmu; concerns; considerations; content; conversations; data; departments; different; discovery; discussions; e800; escience; ethical; ethics; faculty; features; future; https://doi.org/10.7191/jeslib.800; ifla; impact; implementation; important; information; instruction; instructors; intelligence; internal; journal; keenious; liaison; libkey; librarianship; libraries; library; long; march; mellon; n.d; need; new; open; order; plan; potential; practices; privacy; process; product; questions; recommendations; recommender; relevant; research; researchers; resources; services; similar; student; subject; survey; teaching; team; technologies; technology; tool; transparency; understanding; university; users; ways
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9. wolf-ive-2024
   • author: wolf
   • title: wolf-ive-2024
   • date: 2024
   • words: 4464
   • flesch: 30
   • summary: Received: November 15, 2023 Accepted: February 5, 2024 Published: March 6, 2024 Keywords: Beatles, sentiment analysis, optical character recognition, historical newspaper archives, artificial intelligence, AI Citation: Wolff, Milana, Liudmila Sergeevna Mainzer, and Kent Drummond. We performed sentiment analysis on all articles within the dataset using three Python-based natural language processing models.
   • keywords: adam; advanced; analysis; archives; articles; beatles; center; character; code; computing; conclusions; considerations; critical; culture; data; dataset; documents; drummond; e849; escience; ethical; events; fields; general; historical; https://doi.org/10.7191/jeslib.849; journal; language; librarianship; libraries; mainzer; matthew; media; methods; models; negative; new; ocr; optical; original; popular; project; publications; python; recognition; research; researchers; sentiment; sentiment analysis; sentiwordnet; sergeevna; social; sources; strawberry; tesseract; text; textblob; times; university; use; vader; wolff; words; wyoming; york
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