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Record W2118703009 · doi:10.1002/stab.201510333

Architektonisch qualitätvolle Sandwichfassaden für den Büro‐ und Verwaltungsbau

2015· article· de· W2118703009 on OpenAlexaff
Dieter Ungermann, Nicole Fritzsche, Alexander Wiegand, Paul Floerke

Bibliographic record

VenueStahlbau · 2015
Typearticle
Languagede
FieldEngineering
TopicStructural Analysis of Composite Materials
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsArchitectural engineeringEngineeringHumanitiesArt

Abstract

fetched live from OpenAlex

Abstract Im Rahmen des interdisziplinären Forschungsvorhabens FOSTA P977 “Architektonisch qualitätvolle Sandwichfassaden“ [5] wurden die Grundlagen einer architektonisch ansprechenden Systembauweise für Fassaden aus Sandwichelementen mit neuartiger Befestigungstechnik gelegt. Durch die Entwicklung geeigneter Verbindungstechniken konnte das große Anwendungspotential der Sandwichbauweise im Geschossbau herausgearbeitet werden. Der vorliegende Beitrag zeigt daher besonders die technisch‐architektonischen Ergebnisse auf, die zur Schaffung von Fassaden im Geschossbau mit hoher architektonischer Qualität und sozio‐kultureller Akzeptanz führen. High quality sandwich‐panel envelope‐systems for office and multi‐storey buildings. As part of the interdisciplinary research project FOSTA P977 “Architecturally high quality Sandwich‐panel Envelope‐systems” [5], the fundamentals of an architecturally appealing prefabricated system for façades of sandwich panels with a new assembly technology was to be developed. Through the development of suitable connection technologies the huge potential of sandwich constructions in multi‐storey buildings could be obtained. The abstract at hand therefore shows especially technical‐architectural results, which lead to the development of envelope systems for office‐ and multi‐storey buildings with high architectural quality and socio‐cultural acceptance.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.312
Teacher spread0.283 · 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.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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