Magma Reservoirs Feeding Giant Radiating Dike Swarms: Insights from Venus
Bibliographic record
Abstract
Evidence of lateral dike propagation from shallow magma reservoirs is quite common on the terrestrial planets, and examination of the giant radiating dike swarm population on Venus continues to provide new insight into the way these complex magmatic systems form and evolve. For example, it is becoming clear that many swarms are an amalgamation of multiple discrete phases of dike intrusion. This is not surprising in and of itself, as on Earth there is clear evidence that formation of both magma reservoirs and individual giant radiating dikes often involves periodic magma injection. Similarly, giant radiating swarms on Earth can contain temporally discrete subswarms defined on the basis of geometry, crosscutting relationships, and geochemical or paleomagnetic signatures. The Venus data are important, however, because erosion, sedimentation, plate tectonic disruption, etc. on Earth have destroyed most giant radiating dike swarm's source regions, and thus we remain uncertain about the geometry and temporal evolution of the magma sources from which the dikes are fed. Are the reservoirs which feed the dikes large or small, and what are the implications for how the dikes themselves form? Does each subswarm originate from a single, periodically reactivated reservoir, or do subswarms emerge from multiple discrete geographic foci? If the latter, are these discrete foci located at the margins of a single large magma body, or do multiple smaller reservoirs define the character of the magmatic center as a whole? Similarly, does the locus of magmatic activity change with time, or are all the foci active simultaneously? Careful study of giant radiating dike swarms on Venus is yielding the data necessary to address these questions and constrain future modeling efforts. Here, using giant radiating dike swarms from the Nemesis Tessera (V14) and Carson (V43) quadrangles as examples, we illustrate some of the dike swarm focal region diversity observed on Venus and briefly explore some key implications for the questions framed above.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".