Modified spectral format based on probability level using site-specific uniform hazard spectrum
Bibliographic record
Abstract
Abstract Deficiencies of the four spectral formats i.e., 2%/50-yr, 5%/50-yr, 10%/50-yr and AASHTO (American Association of State Highway Officials) 2009 demand modification of the spectral formats for bridge design application in Canada. Among them the 10%/50-yr spectrum is dropped from current investigation as its difference with Canadian Highway Bridge Design Code (CHBDC) 2006 is too large to modify. This study introduces an approach calibrating on the values of elastic seismic response coefficient to provide a new shape of the Canadian bridge design spectrum based on modified 2%/50-yr, modified 5%/50-yr and modified AASHTO spectral formats. A Digital Visual Fortran program was prepared to determine the optimum values of the modification factors incorporated into the three spectral formats calibrated on the data of 389 cities of Canada. Thus, here it is developed the strategies of modifying the three spectral formats based on the best probability level for CHBDC using site-specific Uniform Hazard Spectrum (UHS). Finally, select the most suitable spectral format to apply for the design base shear calculations for the bridges of Canada.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".