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Record W2998347649

Synthesis of Akaganeite in the Presence of Sulfate: Implications for Akaganeite Formation in Yellowknife Bay, Gale Crater, Mars

2016· article· en· W2998347649 on OpenAlexaboutno aff
T. Peretyazhko, Allison C. Fox, B. Sutter, P. B. Niles, Madison Adams, R. V. Morris, D. W. Ming

Bibliographic record

VenueLunar and Planetary Science Conference · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsAkaganéiteMars Exploration ProgramImpact craterGeologySulfateAnhydriteMineralogyGeochemistryChemistryAstrobiologyGoethiteGypsumPhysics
DOInot available

Abstract

fetched live from OpenAlex

Akaganeite (beta-FeOOH) is an Fe(III) (hydr)oxide with a tunnel structure usually occupied by chloride. Akaganeite has been recently discovered in a mudstone on the surface of Mars by the Chemistry and Mineralogy (CheMin) and Sample Analysis at Mars (SAM) instruments onboard the Mars Science Laboratory (MSL) Curiosity Rover in Gale crater [1, 2]. Akaganeite was detected together with sulfate minerals [anhydrite (CaSO4) and basanite (2CaSO4·2H2O)] in the drilled Cumberland and John Clein mudstone samples at Yellowknife Bay [2]. Discovery of akaganeite and sulfates in the same samples suggests that sulfate ions could be present in aqueous solution during akaganeite formation. However, mechanism and aqueous environmental conditions of akaganeite formation (e.g., pH and range of sulfate concentration) in Yellowknife Bay remain unknown. The objective of our work was to perform synthesis of akaganeite without or with sulfate addition at variable pHs in order to constrain formation conditions of akaganeite in Yellowknife Bay, Gale crater on Mars.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.242
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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