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Record W4384829638 · doi:10.36939/ir.202307041523

Spectroscopic Analysis of Ca-Carbonates from Utah Crystal Geyser to Support Carbonate Detection within our Solar System

2023· dissertation· en· W4384829638 on OpenAlexafffund
Z. U. Wolf

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Winnipeg
FundersCanadian Space Agency
KeywordsCalciteAragoniteMineralogyRaman spectroscopyGeologyCarbonateCarbonate mineralsMineralCrystal (programming language)Materials scienceOptics

Abstract

fetched live from OpenAlex

This study investigated the Utah Crystal Geyser, a unique low-temperature, CO2-rich geyser relevant to Mars, icy moons, and asteroids. Samples from the site had a range of textural and color differences; however, they contained similar mineral assemblages dominated by carbonates (calcite and aragonite). The identification of calcite and aragonite is important as they can be biogenically produced and possess the ability to preserve biogenic fingerprints and entomb microbial fossils. This analysis confirmed that the most effective method for identifying and distinguishing calcite and aragonite is through a combination of several techniques. Specifically, reflectance spectroscopy was able to determine the presence of calcite-aragonite mixtures. However, it could not effectively differentiate between the two since the band positions and shapes change subtly with varying abundances of the two carbonates. Thus, it can only be stated that a mixture is present, and the degree to which transformation from aragonite to calcite has proceeded is poorly constrained. Raman spectroscopy was able to identify both calcite and aragonite and could differentiate between the two through diagnostic peaks in the low Raman-shift region of the spectrum. Scanning electron microscopy imaging provided sub-micrometer images of textures and sedimentary fabric, such as laminations, crystal structures, and entombed microbial fossils. X-ray diffractometry and X-ray fluorescence were used to determine and verify the mineralogy of the samples. The low-temperature origin of these carbonates is likely the factor responsible for the lack of homogeneity within the samples. Carbon dioxide degassing is likely the primary factor supporting the precipitation of aragonite at the geyser, despite the low temperature. The results have implications for carbonate detection and characterization on Mars and the recognition of low-temperature carbonate precipitates on a number of planetary bodies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.245
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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