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DataSheet1_Sulfur- and Iron-Rich Mineralogical Features Preserved in Permafrost in the Canadian High Arctic: Analogs for the Astrobiological Exploration of Mars.docx

2022· dataset· en· W6908890207 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldComputer Science
TopicImage Processing and 3D Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsPyritePermafrostWeatheringHematiteMineralCarbonateSulfide mineralsMicaCarbonate minerals

Abstract

fetched live from OpenAlex

<p>Elliptical sulfate-rich features, stained red by the presence of iron oxides, are set within permafrost and carbonate rock at Borup Fiord Pass in the Canadian High Arctic. These features, which vary in diameter from ∼0.5 to 3 m, exhibit the co-localization of sulfur (S) and iron (Fe) minerals, with S and Fe both preserved in multiple oxidation states. Through application of x-ray diffraction (XRD) and Raman microspectroscopy, we find that these features appear to encapsulate central cores with abundant pyrite while S<sup>0</sup>, gypsum, and iron-bearing secondary minerals such as jarosite, goethite, and hematite have formed from oxidative weathering of the pyrite. These features appear similar to terrestrial gossans, mineral features representative of weathered sulfide ores in the near-surface. We use Raman microspectroscopy and scanning transmission x-ray microscopy (STXM) to show that organic carbon is associated with the minerals within these features. The origin of this carbon remains enigmatic; however, we consider the possibility that this carbon, along with etching of the pyrite grains and accumulation of encrusted filaments detected in the features, may be indicative of preserved biological activity during alteration of the pyrite. We also consider how such geological sulfide emplacements and their weathered surface expressions may provide a target for future surface and remote sensing studies of Mars and in the search for extraterrestrial life.</p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.243
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.000

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 head0.055
GPT teacher head0.269
Teacher spread0.214 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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