MétaCan
Menu
Back to cohort
Record W1991341330 · doi:10.1193/012814eqs022m

Nonlinear Rotation of Capacity‐Protected Foundations: The 2015 Canadian Building Code

2015· article· en· W1991341330 on OpenAlexaffabout
Perry Adebar

Bibliographic record

VenueEarthquake Spectra · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNonlinear systemRotation (mathematics)Moment (physics)Structural engineeringFlexibility (engineering)Building codeSeismic analysisCode (set theory)Bearing capacityEngineeringGeotechnical engineeringMathematicsComputer scienceGeometryPhysicsStatisticsClassical mechanics

Abstract

fetched live from OpenAlex

When foundations are capacity‐protected, inelastic deformations will occur primarily in the seismic force‐resisting system. Soil flexibility can be ignored when determining seismic loads, but footings will rotate when subjected to the maximum overturning moment, and this may increase building drifts, particularly in lower stories where gravity‐load columns are less flexible. A “hand calculation” method is presented for estimating rotation of a footing from the uniform bearing stress distribution required to resist the applied overturning moment. The method, which has been adopted in the 2015 Canadian building code, accounts for initial linear rotation of footings and additional nonlinear rotation due to footing uplift and nonlinearity of soil. A quick, safe estimate can be made using approximate equations, or a more accurate estimate can be made by determining two parameters from figures. Design examples demonstrate how the method can be used to design foundations for improved performance at a small additional cost.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.998

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 communication0.0000.000
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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueEarthquake SpectraSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207