Identification and characterization of new feldspar-bearing rocks in the walls of Valles Marineris, Mars
Bibliographic record
Abstract
VNIR spectroscopy has previously led to many discoveries pertaining to Mars geologic history (e.g., the discovery of hydrated minerals associated to ancient terrains with OMEGA, Bibring et al., 2006). Plagioclase feldspar minerals can also be identified with spectroscopic techniques thanks to a 1.3 microns absorption in the VNIR domain (e.g., Adams and Goullaud, 1978). Previous lunar analog studies show however that when mixing powders of Ca plagioclase and a mafic component (olivine or pyroxene), the feldspars absorption band is quickly masked (e.g., Cheek and Pieters, 2014). This study further demonstrates that the 1.3 micron feature is only detectable if the plagioclase abundance is > 90 %. Based on this observation, previous feldspar absorptions on Mars have been interpreted as evidence for nearly pure anorthositic rocks (e.g., Carter and Poulet, 2013). A recent study by Rogers and Nekvasil (2015) however suggests that phenocryst basalts with less than 90% plagioclase could reproduce the 1.3 micron feature if large crystals are involved, although no whole rock measurements were made. In the present study, we describe new feldspar signatures detected with the CRISM VNIR spectral-imager in the walls of the Valles Marineris grand canyon, on Mars. The associated rock textures and elevations were assessed from CTX and HiRISE images and DTMs. In parallel, we are collecting VNIR spectra of various (uncrushed) terrestrial rocks containing a large range of feldspar abundances and grain sizes. Analyses are carried out between 0.35 and 2.5 microns with an ASD Fieldspec at CRPG Nancy, France, and will be presented at the conference time. By combining laboratory measurements of a range of possible terrestrial analog rocks with the study of Mars feldspar-bearing outcrops, we should bring more clues on the nature and origin of these feldspathic rocks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".