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Situated Interaction with Ambient Information: Facilitating Awareness and Communication in Ubiquitous Work Environments

2003· article· en· W31665143 on OpenAlexaboutno aff
Norbert Streitz, Carsten Röcker, Thorsten Prante, Richard Stenzel, Daniel van Alphen, Fraunhofer Ipsi

Bibliographic record

VenuePLoS ONE · 2003
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsnot available
FundersInstitute of Education Sciences
KeywordsSituatedContext (archaeology)Work (physics)Computer scienceHuman–computer interactionContext awarenessArchitectural engineeringUbiquitous computingEngineeringGeographyPhoneArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, we introduce our approach as well as examples of realizations for situated interaction in the context of future work environments. These environments will be populated with a range of smart artefacts. The artefacts and their mutual interaction are designed to facilitate awareness and notification as well as informal communication. They constitute examples of our approach to develop future work environments going not only beyond traditional PC-based work places but also beyond electronic meeting rooms and roomware components previously developed by us. We address a range of spaces in office buildings including semi-public spaces, e.g., in the hallway, the foyer, and the cafeteria. The approach is not restricted to office buildings but can be extended to other types of buildings and spaces. It is part of our vision that we call "Cooperative Buildings". The artefacts and the software were developed in the EU-funded "Disappearing Computer"- project "Ambient Agoras: Dynamic Information Clouds in a Hybrid Worlds".

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.227
Teacher spread0.198 · 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 designBench or experimental
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

Citations84
Published2003
Admission routes1
Has abstractyes

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