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Record W2041214259 · doi:10.1139/l01-092

Fazlur Khan (19291982): reflections on his life and works

2002· article· en· W2041214259 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicSeismic and Structural Analysis of Tall Buildings
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignUniversity of Dhaka
KeywordsTowerPrideArchitectureStructural systemSketchArchitectural engineeringEngineeringCivil engineeringVisual artsArtComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Tall buildings, or skyscrapers, are icons of cities, symbols of corporate power, and a mark of national pride. Certain skyscrapers, such as the John Hancock Center and the Sears Tower in Chicago, are also marvels of engineering that have paved the way for ever increasing heights of structural systems. Since the 1960s, a series of new structural systems has been introduced with the objective of achieving economically-competitive and aesthetically-pleasing tall buildings without compromising safety. One of the great structural engineers responsible for the new structural systems was Dr. Fazlur Rahman Khan. This paper provides a biographical sketch of Dr. Khan and discusses some of his innovations pertaining to high-rise buildings. It shows that his contributions led to a new vertical scale for the modern day city.Key words: aesthetics, architecture, innovation, structural system, tall building.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.632

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 head0.014
GPT teacher head0.187
Teacher spread0.173 · 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