Bibliographic record
Abstract
Assuming that the northern lowland of Mars is created by a giant Borealis impact, I investigate its consequences on the thermal state of the mantle and the core dynamo for four different impact models using the scaling laws of crater formation, the shock pressure model of Pierazzo et al. (1997), and the “foundering” shock heating model of Watters et al. (2009). The impact heating enhances the temperature of the mantle by 1000–3000 K down to ∼1000 km depth. The superheated upper mantle ascends rapidly as a giant plume and develops a strong convection in the entire mantle of the subimpact hemisphere, while the antipodal hemisphere remains almost undisturbed for the period of 100 Myr considered in this study. The upwelling of the plume rapidly sweeps up the impact‐heated base of the mantle and replaces it with the cold surroundings, reducing the effects of the impact‐heated mantle on the heat loss of the core. However, direct shock heating stratifies the core and effectively suppresses a preexisting thermal convection in the core. This cripples a preexisting thermally driven core dynamo. It takes 35–85 Myr for the stratified core model to exhaust impact heat and resume global convection and possibly regenerate a strong dynamo. Adding the superheated iron content of an impactor on the core does not create an appreciable dynamo but elongates the heat exhaustion time and delays the regeneration of a strong dynamo by an additional ∼40 Myr. It is concluded that Borealis impact, if it occurred, could have crippled the core dynamo of Mars for up to ∼70–120 Myr.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".