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Record W4223610816 · doi:10.1002/bate.202100117

In Brettsperrholz eingeklebte Stahlgewindestäbe – Experimente, numerische Simulation und Traglastbestimmung

2022· article· de· W4223610816 on OpenAlexaff
Till Vallée, Thomas Tannert

Bibliographic record

VenueBautechnik · 2022
Typearticle
Languagede
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsGynecologyPhysicsHumanitiesPhilosophyMedicine

Abstract

fetched live from OpenAlex

Abstract Der Holzbau überschreitet derzeit neue Grenzen hinsichtlich Dimensionen und architektonischer Möglichkeiten, wie die weltweit zunehmende Zahl von Hochhäusern zeigt. Ermöglicht wird dies durch hochleistungsfähige Verbindungen, wie z. B. eingeklebte Stäbe (aus Stahl und Faserverbundwerkstoffen), und Holzwerkstoffe, wie z. B. Brettschichtholz (BSH), wo alle Brettlagen parallel verleimt sind, oder Brettsperrholz (BSP), welches aus mehreren, kreuzweise flach aufeinander verleimten Brettlagen besteht. Dieser Beitrag beleuchtet den aktuellen Stand von in BSP eingeklebten Stahlgewindestäben und zeigt eine Übersicht über jüngste experimentelle und numerische Ergebnisse. Es werden die Gemeinsamkeiten, aber auch Unterschiede im Vergleich zu in BSH eingeklebten Stahlstäben aufgezeigt, die sich aufgrund der verschiedenen Orientierung der einzelnen Lagen ergeben. Ein weiterer Schwerpunkt liegt auf der Vorhersage der Traglast, für die derzeit nur sehr wenige Ansätze verfügbar sind.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.266
Teacher spread0.247 · 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 designSimulation or modeling
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

Citations2
Published2022
Admission routes1
Has abstractyes

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