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Record W1513670302

Categorically speaking:reflecting AEC/FM participants' requirements in Groupware

2003· book-chapter· en· W1513670302 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAston Publications Explorer (Aston University) · 2003
Typebook-chapter
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsNational Research Council CanadaUniversity of New Brunswick
Fundersnot available
KeywordsCategorizationCollaborative softwareKnowledge managementComputer scienceEngineeringArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Groupware allows participants in an AEC/FM project to timely share relevant electronic project information at near real-time speed. One challenge of existing groupware tools is the varying information categorization needs of different AEC/FM project participants within the same groupware environment. This paper introduces initial results of a survey of several AEC/FM companies' project information categorizations. These initial results reveal differences in the ways AEC/FM project participants organize project information within each company. These differences will result in the need for a comprehensive information categorization solution when companies move their organized company specific project information to a project-wide repository in groupware. In the future, as a result of this research, a comprehensive project categorization scheme will be introduced which would allow participant-specific views of the AEC/FM project information to be rendered.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
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 head0.143
GPT teacher head0.290
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