MétaCan
Menu
Back to cohort
Record W2047001853 · doi:10.1139/l02-087

Load factor calibration for the proposed 2005 edition of the National Building Code of Canada: Statistics of loads and load effects

2003· article· en· W2047001853 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.

fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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 · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsnot available
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsWind engineeringBuilding codeStructural loadSnowLoad factorCalibrationStructural engineeringStatisticsOccupancyEngineeringMeteorologyCivil engineeringMathematicsGeography

Abstract

fetched live from OpenAlex

The 2005 edition of the National Building Code of Canada (NBCC) will adopt a companion-action format for load combinations and specify wind and snow loads based on their 50 year return period values. This paper summarizes statistics for dead load, live load due to use and occupancy, snow load, and wind load that have been adopted for calibration, and a companion paper presents the calibration itself. A new survey of typical construction tolerances indicates that statistics for dead load widely adopted for building code calibration are adequate unless the dead load is dominated by thin, cast-in-place concrete toppings. Unique statistics for live load due to use and occupancy are derived that pertain specifically to the live load reduction factor equation used in the NBCC. Statistics for snow and wind loads are normalized using the 50 year values that will be specified in the 2005 NBCC. New statistics are determined for the factors that transform wind speeds and ground snow depths into wind and snow loads on structures.Key words: buildings, code calibration, companion action, dead loads, live loads, load combinations, load factors, reliability, safety, snow loads, wind loads.

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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
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 head0.027
GPT teacher head0.247
Teacher spread0.219 · 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