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Record W1918627805 · doi:10.21083/partnership.v3i2.877

New Talking Avatars on the MSVU Library Website

2008· article· en· W1918627805 on OpenAlexaffvenue
Hilary Skov-Nielsen

Bibliographic record

VenuePartnership The Canadian Journal of Library and Information Practice and Research · 2008
Typearticle
Languageen
FieldComputer Science
TopicAI in Service Interactions
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsAvatarScripting languageWorld Wide WebComputer scienceService (business)SoftwareClothingProcess (computing)The InternetMultimediaHuman–computer interaction

Abstract

fetched live from OpenAlex

Two talking avatars --Sarah and Suzie SitePal --were recently added to the MSVU Library website.By adding the avatars to the site, the Library hopes to make the site more interactive and fun for new and returning students.The avatars are used to welcome students to the Library, to highlight Library resources and services, and to relay information about Library events.The SitePal software was installed by Denyse Rodrigues, and the avatars were designed and scripted by myself, the Library's new term librarian responsible for public services.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0660.021

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.315
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2008
Admission routes2
Has abstractyes

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Same venuePartnership The Canadian Journal of Library and Information Practice and ResearchSame topicAI in Service InteractionsFrench-language works237,207