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Record W2061184746 · doi:10.1108/eum0000000005741

Designing and developing multimedia CD‐ROMs: lessons from the <i>Treasures of Islam</i>

2001· article· en· W2061184746 on OpenAlexaff
Jamshid Beheshti, Andrew Large, Haidar Moukdad

Bibliographic record

VenueOnline Information Review · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsExhibitionComputer scienceIslamInterface (matter)MultimediaMetaphorWorld Wide WebVideo editingInclusion (mineral)User interfaceVisual artsArtSociologyHistoryLinguisticsOperating system

Abstract

fetched live from OpenAlex

A multilingual and multimedia CD‐ROM containing rare Islamic works of art is designed and produced under fiscal constraints. The disparate rare materials are organised and presented through an intuitive interface based on a book metaphor for a diverse audience. The major portion of the cost (35 percent) was devoted to digitising the images, texts, audio and video segments. Approximately 20 percent of the production team’s time was spent on interface design, while an equal amount of time was spent on analysing and organising the collection of materials for inclusion in the CD‐ROM. The procedure and associated costs for developing this digital exhibition are discussed.

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)0.007
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.377
Teacher spread0.306 · 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".

Quick stats

Citations4
Published2001
Admission routes1
Has abstractyes

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