Scientific Exploration of Induced SeisMicity and Stress (SEISMS)
Bibliographic record
Abstract
Abstract. Several major fault-drilling projects have captured the interseismic and postseismic periods of earthquakes. However, near-field observations of faults immediately before and during an earthquake remain elusive due to the unpredictable nature of seismicity. The Scientific Exploration of Induced SeisMicity and Stress (SEISMS) workshop met in March 2017 to discuss the value of a drilling experiment where a fault is instrumented in advance of an earthquake induced through controlled fluid injection. The workshop participants articulated three key issues that could most effectively be addressed by such an experiment: (1) predictive understanding of the propensity for seismicity in reaction to human forcing, (2) identification of earthquake nucleation processes, and (3) constraints on the factors controlling earthquake size. A systematic review of previous injection experiments exposed important observational gaps in all of these areas. The participants discussed the instrumentation and technological needs as well as faults and tectonic areas that are feasible from both a societal and scientific standpoint.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".