Understanding pre-eruptive patterns: the rock physics interpretation
Bibliographic record
Abstract
Changes of seismic wave velocities, rates of seismicity and different types of seismic signals are routinely observed before eruptions in volcanic areas. Anomalies and rapid changes of geophysical parameters have been interpreted as rapid changes of the mechanical properties of the medium and/or of magmatic pressurization (e.g. coupling of dyke emplacements and fracturing of the medium). A thorough assessment of the physical properties of volcanic rocks and an improved understanding of the complex coupling between mass/heat transfer mechanisms and rock deformation/failure processes has been revealed to be essential for the interpretation of the geophysical signatures monitored in volcanic areas. For instance seismic tomography had greatly benefit from simultaneous measurements of P and S wave velocities at simulated ‘in situ’ stress conditions, while time-to-failure models were supported from a deeper knowledge of the changes of mechanical and physical properties as a function of incremental thermal and mechanical damage. Luigi had the first great intuition that laboratory simulations could allow us to rebuild the physical mechanisms responsible for a given seismic signal, thus providing invaluable quantitative information for understanding and discriminating the different seismic signals observed before volcanic eruptions. A direct relationship between seismic waveforms + spectrograms and physical phenomena was assessed, by scaling length and frequency between the laboratory and the field. Departing from the first data set of seismic signals related to magma emplacement generated from the work with Luigi, we obtained crucial advances where simulated volcanic conditions of corresponding geophysical parameters have been directly measured, while reproducing deformation, fluid decompression and hybrid mechanisms acting in volcanic areas. This provided a solid and well-constrained new experimental insight into the developing damage leading to faulting and geophysical signatures related to fluid flow and to the role of supercritical phases. The close agreement between laboratory and nature allows us to open a new research field where geophysical signatures can be directly linked to physical processes tested in the laboratory where these processes are very well constrained.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".