MétaCan
Menu
Back to cohort
Record W3011376274

SEISMIC ANALYSIS OF BUILDING USING DIFFERENT COUNTRY CODES: A REVIEW

2018· review· en· W3011376274 on OpenAlexaboutno aff
Ankush R. Kene, Ashok R. Mundhada

Bibliographic record

VenueJournal of Emerging Technologies and Innovative Research · 2018
Typereview
Languageen
FieldEngineering
TopicSeismic and Structural Analysis of Tall Buildings
Canadian institutionsnot available
Fundersnot available
KeywordsSeismic analysisCode (set theory)Prima facieBuilding codeEarthquake engineeringEngineeringEarthquake scenarioSeismologyCivil engineeringStructural engineeringComputer scienceGeologySeismic hazardLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Seismic codes are very important in the designing of multistoried buildings. In order to design an earthquake resistant building, structural engineers must have the good knowledge of the various seismic codes. In this study, seismic design provisions in five building codes, IS 1893-2002 (Part-1), Japan (AIJ), 1997 USA (UBC), Canadian (NRC 2005) and 2009 USA (IBC) and their similarities and differences are reviewed. American seismic design code was first to be introduced in the world in 1927, after the California earthquake. Great advances in the building standards in different countries make it possible for their comparison. Factors like Importance factor, response reduction factor, seismic zones, soil profile, Fundamental time period, base shear will be compared. Prima facie, after the study performed it looks like the Japanese code is the most advanced code in the world. Indian and American codes are quite similar, while there is a huge difference in the Japanese and rest of the codes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.107
GPT teacher head0.423
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Emerging Technologies and Innovative ResearchSame topicSeismic and Structural Analysis of Tall BuildingsFrench-language works237,207