How did hydraulic-fracturing operations in the Horn River Basin change seismicity patterns in northeastern British Columbia, Canada?
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
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.
Bibliographic record
Abstract
Abstract An increase in regional seismicity has been documented for the Horn River Basin (HRB) since the development of shale gas began in late 2006. Operational parameters of all hydraulic-fracturing (HF) treatments in the HRB between November 2006 and December 2011 were compiled from completion reports collected by the British Columbia Oil and Gas Commission (BCOGC). This database was compared with regional earthquake catalogs to delineate a quantitative relationship between the observed variation of regional seismicity and local HF operations. Taking the HRB as a whole, results suggest that the total injected volume from hydraulic fracturing is a more significant factor in affecting the pattern of local seismicity than injection pressure is. However, no clear change in background seismicity can be observed when the total monthly injected volume is less than ∼ 20,000 m3. The initial effect of increasing injected volume is an increase in earthquake frequency but not magnitude. Relatively large seismic- moment release (> 1014 N m) occurred only when the monthly injected volume exceeded ∼ 150,000 m3. Variable time lags, from days to four months, are observed between intense HF and the occurrence of a significant local earthquake. The hydrologic properties of the source formations and local geologic conditions (such as distribution, geometry, and dimension of preexisting faults) also might play important roles in induced seismogenesis, in addition to the total volume of injection.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it