Investigating the Lake Bosumtwi impact structure: Insight from numerical modeling
Bibliographic record
Abstract
The current topography of the Lake Bosumtwi crater and some of its structural dimensions have been determined by geophysical methods. We combine these data with sophisticated numerical models to evaluate the cratering process itself (for example, melt and tektite generation) as well as to test the modeling code. The geophysical maps show some asymmetry in plan view, with the main anomaly north of the crater center. The simulations of the early stage show asymmetric patterns only in ejecta and tektite distributions, while the late stage is modeled for the vertical impact without any asymmetry. We estimate the projectile size from scaling laws and then, varying material properties, reproduce a crater, which is similar to the Bosumtwi, but too deep. Bulking allows us to reconcile differences between the model results and the observed topography. Shock melt estimates are in good agreement with the Bosumtwi magnetic signature. Modeled distribution of tektites assumes an impact angle of 30°–45° and an impact direction from the N‐NE. The combination of numerical models and field evidence not only provides necessary information for upcoming scientific drilling of the structure but also suggests interesting and well‐suited drill sites. Besides the central uplift and the annular moat with a suggested thick breccia cover, drilling at the location of the geophysical anomalies and comparison of downrange and transversal locations will provide new insight into preimpact and impact‐induced asymmetries.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".