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Record W1552937981 · doi:10.19173/irrodl.v7i2.369

Portable Applications in Mobile Education

2006· article· en· W1552937981 on OpenAlexaffvenue
Jon Baggaley

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2006
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsAthabasca University
Fundersnot available
KeywordsComputer scienceMultimediaUSBThe InternetWorld Wide WebPresentation (obstetrics)File transferSoftwareMobile deviceField (mathematics)Transfer (computing)Operating system

Abstract

fetched live from OpenAlex

Portable software applications can be carried on a convenient storage medium such as a USB drive, and offer numerous benefits to mobile teachers and learner. The article illustrates the growing field of ‘portable apps’ in reviews of seven contrasting products. These represent the major categories of document editing, email maintenance, Internet browsing, instant messaging, file transfer, multimedia presentation, and anti-virus protection. Emphasis is placed on ways to use ‘portable apps’ to overcome the common problems of Internet usage during travel.

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)0.003
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 score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.003
Scholarly communication0.0070.007
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0240.015

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 head0.036
GPT teacher head0.423
Teacher spread0.388 · 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
Published2006
Admission routes2
Has abstractyes

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