Bibliographic record
Abstract
Coupling is a convenient word that describes a wide variety of interactions or feedback processes, including those that we do not fully understand. Examples in Earth science include ocean‐atmosphere coupling, climate‐tectonics coupling, and core‐mantle coupling. The word is also very popular in discussions of plate boundary earthquake processes. As a vague expression, fault coupling is a perfectly adequate term, describing some kind of mechanical interaction between rocks of each side of a fault. For those of us who try to infer fault processes from geodetic measurements, coupling usually indicates a state of no or low current slip. If a fault is fully locked, we may say it is “coupled” or “fully coupled.” If a plate boundary fault is slipping at the long‐term plate convergence rate, we may say it is “decoupled.” Fault segments that are slipping more slowly than the plate convergence rate are then “partially” coupled. To avoid awkward expressions such as “negatively” or “overly” coupled, an equivalent description has been used in the literature; that is, to define a “coupling ratio” with values ranging from negative to greater than unity. For describing kinematics, these expressions would not be wrong. However, with one additional step, our usage of the word coupling can lead to confusion. That step is to describe a fault that is not slipping as “strongly coupled.”
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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.008 | 0.033 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".