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Record W1514600942

Cooperative Hypermedia Management Systems

2006· article· en· W1514600942 on OpenAlexaff
Janet Verbyla, Carolyn Watters

Bibliographic record

VenueTexas Digital Library (University of Texas) · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceHypertextHypermediaWorld Wide WebRetrofittingHuman–computer interactionMultimedia
DOInot available

Abstract

fetched live from OpenAlex

The benefits of including hypertext functionality in application systems have become widely accepted. Users expect applications to provide browsing and linking capabilities to augment search and command capabilities. Three approaches to providing such environments are feasible. The first two of these involve retrofitting hypertext functionality to third-party applications, and building an 'open' hypertext system that manages the integration of third-party applications with hypertext. The third approach involves building a task-oriented environment that enables a hypertext management system to be constructed, building block style, using third-party applications as building units that cooperate in the delivery of the required functionality. The paper argues that the last of these approaches, cooperative hypermedia management systems, is the most realistic. A model for such systems is described. Issues involved in designing and building such systems are discussed and examples presented.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0080.008
Open science0.0030.006
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0140.004

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 head0.008
GPT teacher head0.155
Teacher spread0.147 · 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 designSimulation or modeling
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

Citations2
Published2006
Admission routes1
Has abstractyes

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