Bibliographic record
Abstract
What can seismic waves tell us about Earth's history?Studying the hidden structure of our planet is essential for understanding Earth's geological past and predicting its future.Dr Fiona Darbyshire, a seismologist at the Université du Québec à Montréal in Canada, is using seismic waves to model Earth's rocky, outer layer and investigate the processes that have shaped our continents over billions of years.Seismology Talk like a... seismologist PROFILE Crust -the thin, outermost layer of Earth, made of solid rock and forming the continents and ocean floors Lithosphere -the rigid outer layer of Earth, made up of the crust and part of the upper mantle Mantle -the layer beneath the Earth's crust, consisting of hot rock that, although solid, moves slowly over geological time Seismograph -an instrument used to detect and record seismic waves Seismometer -the specific part of the seismograph that detects ground movement Seismic waves -vibrations that travel through Earth's interior, caused by various sources like earthquakes or explosionsTectonic activity -the movement and interaction of Earth's tectonic plates, which causes earthquakes, volcanic eruptions, and the formation of mountains Mantle plume -a column of hot, buoyant rock rising from deep within the Earth's mantle that can cause volcanic activity and affect the lithosphere
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.018 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".