Hierarchical clustering of pit crater chains on Venus
Bibliographic record
Abstract
Composed of a series of circular to elliptical bowl-shaped depressions, pit crater chains are common on the surface of many of our solar system’s terrestrial planets and moons. Using Magellan synthetic aperture radar (SAR) images, four areas of Venus are examined in which a total of 354 pit crater chains are found: Ganiki Planitia (180°E–210°E, 25°N–50°N), Ulfrun Regio (200°E–240°E, 0°N–25°N), Themis Regio (270°E–300°E, 25°S–40°S), and Idunn Mons (205°E–225°E, 35°S–55°S). A study of the distribution of these pit crater chains at regional and local scales reveals hierarchical clustering. On a regional scale, pit crater chain clusters are associated with graben–fissure systems that are radiating (associated with volcano-tectonic features), circumferential (associated with coronae), and linear (with uncertain volcano-tectonic genesis). At a local scale, pit crater chains are found with marked restriction to particular portions of graben–fissure systems. We conclude that this hierarchical clustering is an indication that both an extensional process and a lithological control contribute to the formation of pit crater chains. Specifically, we propose that pit crater chain formation on Venus occurs in poorly welded volcaniclastic material (e.g., shield plains material unit) that has been crosscut by graben–fissure system(s). Only portions of the shield plains material unit may have sufficient thickness of volcaniclastic material, thus explaining the lack of a co-extensive relationship. Additionally, pit crater chains in other map units may be explained by shallow burial of the volcaniclastic material.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".