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Record W4293085249 · doi:10.1002/bate.202200005

Erdbebenanker für Massivholzkonstruktionen

2022· article· de· W4293085249 on OpenAlexaff
Thomas Tannert

Bibliographic record

VenueBautechnik · 2022
Typearticle
Languagede
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Abstract Der Holzbau überschreitet derzeit neue Grenzen, besonders in Bezug auf mehrgeschossige Konstruktionen. Wegen der zu berücksichtigenden höheren Wind‐ und Erdbebenlasten sind Hochhäuser mit erhöhten Anforderungen konfrontiert, unter anderem müssen die Erdbebenanker (EA) hohe Tragfähigkeit aufweisen, um diese Lasten abzuleiten, eine hohe Steifigkeit, um horizontale Verschiebungen zu minimieren, sowie Nachgiebigkeit, um die gewünschte Kinematik der aussteifenden Wandplatten während eines Erdbebens zu ermöglichen. In diesem Beitrag wird der Stand der Technik in der EA‐Technologie für aussteifende Massivholzwände zusammengefasst sowie aktuelle Forschungsergebnisse zu drei innovativen EA präsentiert: i) mit Vollgewindeschrauben oberflächeninstallierte Stahlplatten, ii) eingeschlitzte und mit selbstbohrenden Stabdübeln befestigte Stahllochplatten und iii) hyperelastische Platten mit Stahlstangen.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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
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
Published2022
Admission routes1
Has abstractyes

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