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Record W4391786677 · doi:10.1002/9781394213313.ch56

The Robert L. Preger Intelligent Workplace<sup><scp>TM</scp></sup>a Transformative Living Laboratory at Carnegie Mellon University

2024· other· en· W4391786677 on OpenAlexaff
Volker Hartkopf, Vivian Loftness

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsWorkplace Health, Safety and Compensation Commission
FundersElectricité de FranceU.S. Department of StateU.S. General Services AdministrationTechnische Universität MünchenTsinghua UniversityU.S. Environmental Protection AgencyPPG IndustriesCarnegie Mellon UniversityU.S. Department of DefenseU.S. Department of EnergySteelcaseNational Science Foundation
KeywordsTransformative learningEngineeringEngineering physicsSociologyPedagogy

Abstract

fetched live from OpenAlex

Climate change, rapid advances in technology, and the global pandemic have significantly changed the nature of work and the workplaces that are best suited to ensuring a healthy, productive workforce. The Robert L. Preger Intelligent Workplace™ (IW) is a 700 m 2 living laboratory of component and subsystem innovations in an occupied, lived-in laboratory with integrated passive-active systems for sustainability. The IW enables the interchangeability and side-by-side demonstrations of innovations in HVAC, enclosure, lighting, interior, networking and control components and assemblies. Every Architecture, Building Science, and Building Engineering program should have an IW, a living laboratory of innovative component and subsystem, and a testing ground for the next generation of building systems integration for indoor environmental quality and resource sustainability. The “living laboratories” should be seen as scientific instruments to rival engineering and science labs, support ongoing collaboration with the building industry for research and education of a new generation of building scientists and FM practitioners.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.065
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.012

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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