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Record W1998676845 · doi:10.1504/ijeh.2008.018919

Developing a Web 2.0 Telemedical Education System: the AJAX-Cocoon Portal

2008· article· en· W1998676845 on OpenAlexafffund
Sabah Mohammed, Ahmed Husseini Orabi, Jinan Fiaidhi, Mohamed Ahmed Orabi, Rachid Benlamri

Bibliographic record

VenueInternational Journal of Electronic Healthcare · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAjaxWorld Wide WebComputer scienceWeb 2.0Web serviceMultimediaXMLJavaScriptWeb applicationSemantic WebWorkflowDatabase

Abstract

fetched live from OpenAlex

Web 2.0 technologies such as wikis, podcasts/vodcasting, blogs and semantic portals could be quite effective tools in e-learning for health professionals. If effectively deployed, such tools can offer a way to enhance students', clinicians' and patients' learning experiences, and deepens levels of learners' engagement and collaboration within medical learning environments. However, Web 2.0 requires simplicity of use as well as integration with modern web technologies. This article presents a Web 2.0 telemedical portal, which provides a social community-learning paradigm from the desk of the physician, the student, the hospital administrator, or the insurer. The presented portal utilises RESTful web services and techniques like content syndication, mushups and Asynchronous JavaScript API and XML (AJAX). The designed portal is based on the Apache Cocoon RESTful framework for sharing Digital Imaging and Communications in Medicine (DICOM) medical case studies. Central to this article is the integration between Cocoon and AJAX. The proposed AJAX-Cocoon portal utilises a JSP portlet architecture, which manages the interaction dynamics and overcomes the shortcomings of the JSR 168 and WSRP 1.0 standards.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.435
Teacher spread0.355 · 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 teacher head, 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

Citations5
Published2008
Admission routes2
Has abstractyes

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