Crustal structure of onshore-offshore Iberia, Morocco, and their rifted continental margins, from constrained 3-D gravity inversion using variable mesh depths
Bibliographic record
Abstract
A new onshore-offshore 3-D constrained gravity inversion methodology that incorporates onshore topography and laterally variable inversion mesh depths is used to determine the crustal density distributions, Moho depths, and crustal thicknesses of Iberia, Morocco, and their respective rifted continental margins. The results largely show an excellent correspondence with crustal characteristics determined from sparsely distributed controlled-source and passive seismic experiments, while also allowing the layered density structure of the region to be explored and analyzed in terms of upper, middle, and lower crustal layers. These detailed regional views as a function of depth can improve characterization of crustal types (continental versus oceanic versus transitional), and the resulting interpretations can be directly compared against equivalently derived crustal characteristics for onshore-offshore Atlantic Canada, which encapsulates both Iberia’s and Morocco’s conjugate rifted margins. Collectively, the conjugate 3-D crustal-scale density models allow for the extraction of mega-transects across both sides of the southern North Atlantic, joined together back through geological time using kinematic plate reconstructions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".