Level 3: Seismic Evaluation Guidelines (SEG) for existing buildings in Canada
Bibliographic record
Abstract
"The Level 3 – Seismic Evaluation Guidelines (SEG) supersedes “Guidelines for Seismic Evaluation of Existing Buildings” published by the National Research Council Canada (NRC) in 1993. It is intended to to assist structural engineers in evaluating the compliance of existing buildings with selected performance objectives. The Level 3 – SEG offers comprehensive guidance for three-tiered evaluation procedures, including Tier 1 Quick Evaluation, Tier 2 Deficiency-Based Evaluation, and Tier 3 Detailed Evaluation. While the Tier 1 and Tier 2 procedures adopt force-based approaches consistent with the NBC and CSA design standards to identify and analyze potentially deficient components in a building, the Tier 3 evaluation procedure allows the use of both force-based and performance-based approaches to systematically analyze the building as a whole. To aid structural engineers in the process of moving from seismic evaluation to seismic upgrading, the Level 3 – SEG has been made compatible with a companion document entitled “Seismic Upgrading Guidelines (SUG) for Existing Buildings in Canada” recently published by the NRC . The SUG aims to assist structural engineers in selecting appropriate upgrading techniques to address the identified seismic deficiencies through the seismic evaluation process and demonstrating the compliance of the upgraded buildings with selected performance objectives."
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".