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Nailed Connection Behavior in Light-Frame Wood Shear Walls with an Intermediate Layer of Insulation

2016· article· en· W2320235524 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

VenueJournal of Structural Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsMaterials scienceStiffnessComposite materialStructural engineeringShear wallShear (geology)Framing (construction)Engineering

Abstract

fetched live from OpenAlex

The shear strength and stiffness of light-frame wood shear walls is highly dependent on the behavior of their individual nailed connections. Eighty-four nailed connection specimens were tested under shear loading to determine the effect of including rigid insulation as an intermediate material between the sheathing and framing elements in a light-frame wood shear wall. Each specimen contained common 10d or 16d nails, 15.9 mm oriented strandboard sheathing, spruce-pine-fir lumber, and rigid insulation in varied thicknesses between 0 and 38.1 mm. From the load-deformation results, maximum load, yield load, and stiffness were assessed using curve-fitting and yield-point determination methods. The results indicate that, as the insulation thickness increases, the connection strength and stiffness both exhibit a steep reduction. In addition, nonlinear two-dimensional (2D) finite-element models of the same nailed connections were developed. These models showed good correlation with experimental data and served to confirm that the decline in strength and stiffness observed in the tests is due to the introduction of the insulation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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