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Record W2095638478 · doi:10.1109/sitis.2009.67

Proposal and Evaluation of Adaptive Multimedia Utilization Method for Reliable Web Based Collaboration

2009· article· en· W2095638478 on OpenAlexaff
Yoshitaka Sakurai, Kinshuk Kinshuk, Sabine Graf, Ardah Zarypolla, Kouhei Takada, Rainer Knauf, Setsuo Tsuruta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsAthabasca University
Fundersnot available
KeywordsComputer scienceMultimediaPresentation (obstetrics)Domain (mathematical analysis)Web applicationCognitive loadCognitionWorld Wide Web

Abstract

fetched live from OpenAlex

Due to the geographical distribution, different cognitive capacity, and different domain competency of workers or learners, many misunderstandings can occur during Web based remote collaboration, leading to inefficient discussions and undesired results. To overcome these problems, a “Multimedia adaptive utilization” framework for dependable web based collaboration is proposed and evaluated. This assesses situations of remote users through fusing information of multiple biological sensors and the related contexts such as user profiles. Transmitting and using such information, the system adaptively supports Web based remote collaboration by stressing, warning, and presenting keywords/ summaries in multimedia. Then, effects of adaptive keyword/summary presentation are evaluated as to cognitive profiles of users such as short term memory capacity and associative learning skills when misunderstanding possibilities are estimated on the Web. These evaluations totally demonstrate the feasibility and usefulness of the proposed method.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.952
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.125
GPT teacher head0.479
Teacher spread0.354 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2009
Admission routes1
Has abstractyes

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