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Record W1997464266 · doi:10.1139/l01-070

Performance of buildings during the 2001 Bhuj earthquake

2001· article· en· W1997464266 on OpenAlexvenueno aff
Jag Mohan Humar, David T. Lau, Jean-Robert Pierre

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMasonryInfillReinforced concreteGeologyGeotechnical engineeringEngineeringForensic engineeringStructural engineering

Abstract

fetched live from OpenAlex

The performance of buildings during the January 26, 2001, earthquake in the Kachchh region of the province of Gujarat in India is discussed. A majority of the buildings in the earthquake region were either of load-bearing masonry or reinforced concrete framed structure. Most of the masonry buildings were built with random or coursed stone walls without any reinforcement and heavy clay tile roofing supported on wooden logs. A large number of such buildings collapsed leading to widespread destruction and loss of life. Many reinforced concrete frame buildings had infill masonry walls except in the first storey, which was reserved for parking. As would be expected, the open first storey suffered severe damage or collapsed. Observations of failures confirmed the vulnerability of some structural details that are known to lead to distress. However, an important observation to come out of the earthquake was that masonry infills, even when not tied to the surrounding frame, could save the building from collapse, provided such infills are uniformly distributed throughout the height so that abrupt changes in stiffness and strength did not occur.Key words: Bhuj earthquake, 2001; seismology of Kachchh; earthquake damage survey; performance of buildings; load bearing masonry; reinforced concrete frames; structural details vulnerable to earthquakes.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.004
GPT teacher head0.153
Teacher spread0.149 · 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 designObservational
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

Citations54
Published2001
Admission routes1
Has abstractyes

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