Bibliographic record
Abstract
Within British Columbia's north coast, specifically between Prince Rupert and Bella Bella, from the western coastline to the eastern extent of the Coast Mountains, there has been minimal research to understand earthquake hazards (Brillon, 2016). A more detailed understanding of where and how regional strain energy is being accumulated in the crust and the likelihood of damaging earthquakes in this area is necessary to estimate ground shaking and other earthquake-related hazards. To improve the understanding of seismic hazard in the area, five monitoring stations consisting of seismic and GPS instrumentation were installed in August 2014. In addition, a soft soil seismograph to measure effects of local site conditions was installed in Kitimat and improvements to older GPS and seismic stations in the region were carried out. During the first winter of the deployment a number of the stations suffered significant weather-related damages that resulted in long periods of station downtime. By June 2015 all the stations were repaired and reinforced to minimize damages the following winter. Aside from the stations located in Kitimat, the background noise levels are within the Petersen high and low noise models (Peterson, 1993). The low seismic noise levels consistently allow earthquakes offshore Haida Gwaii with magnitudes less than M2.0 to be used in analysis. In addition to these events 145 earthquakes within the study area have been located. Although a number of earthquakes have been located in the north coast, the locations do not identify any new seismically active areas.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.022 |
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".