Travertine and tufa from Dalhousie Springs (Australia)—Implications for recognizing Martian springs
Bibliographic record
Abstract
Thermal spring deposits are features of considerable interest to Mars scientists because of their potential as astrobiological oases and as records of the paleohydrology of the planet. Terrestrial counterparts can assist in recognizing such features on Mars and in developing technologies for their study and sampling. In this paper, we describe one such analog, the Dalhousie Springs complex in central Australia. The Dalhousie Springs complex is one of largest groundwater discharge landforms known on Earth. It is a carbonate-limited precipitation system due to the non-supersaturated ascending water. Spring carbonates are deposited as discrete mounds and outflow channels resting unconformably on older units. Although subject to postformation geomorphic modification, the spring deposits persist in the landscape and are recognizable long after the parental spring has shut down. We identify 14 specific microfacies belonging to seven facies, which form three environmental associations related to specific depositional environments. Diagenesis has occurred in several stages, as evidenced by distinctive textures on the deposits. Spring deposits on Mars would potentially be recognized by similar textures (although compositions may be quite different) and similar geomorphic relationships. However, in satellite images, spring deposits may be difficult to differentiate from deposits resulting from other processes that produce similar geomorphic features, including mud volcanoes, pingos, and rootless cones. Mineralogical data may assist, but ultimately ground truth will be required.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".