IMPACT FROM A NEARBY SEISMICALLY-ACTIVE FAULT TO SEISMIC HAZARD IN VICTORIA, CANADA
Bibliographic record
Abstract
The description of the Leech River fault (LRF) and the probabilistic seismic hazard analyses (PSHA) presented in this paper were preliminary findings.The LRF has been proven to be seismically inactive in multiple research papers (Morell et al. 2017; 2018 , Li et al., 2018) ) and was erroneously presented as seismically active here.Rather, an area of high-angle transpressional faulting within the Leech River Valley, referred to as the Leech River Valley fault zone (LRVFZ), is the source of seismic activity (Kukovica et al., 2019).The introduced active LRF here should be considered as the LRVFZ.The geometry of the introduced active fault zone does not change.PSHA in this paper utilized two different sets of ground motion prediction equations (GMPEs) to characterize the seismicity of the LRVFZ with fault source zone GMPEs suggesting the LRVFZ increases the Victoria hazard by a factor of 2.65.This estimation is greatly overpredicted due to an error in the input file for the EQHAZ software.The total number of entry points used to describe the fault source zone GMPEs exceeded the coded limit allowed for EQHAZ.Therefore, the presented results for the fault source zone GMPEs in Table 1 and Figure 3 do not accurately represent the total increase in hazard due to the LRVFZ.Accurate simulations of the LRVFZ with fault source zone GMPEs increase the pseudo-spectral accelerations (PSA) at Victoria on average by 11% at 10 Hz and 9% for PGA (Kukovica et al., 2019).More information regarding the seismic hazard of the LRVFZ can be found in Kukovica et al., (2019) or Kukovica, (2019).Kukovicia, J., Considering a seismically active Leech River Valley fault zone in southwestern British Columbia,
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".