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Record W2772366621 · doi:10.1002/9781119227250.ch6

Crystallization of Baddeleyite in Basaltic Rocks from Mars, and Comparisons with the Earth, Moon, and Vesta

2017· other· en· W2772366621 on OpenAlexaff
C. D. K. Herd, D. E. Moser, K. T. Tait, James Darling, Barry Shaulis, T. J. McCoy

Bibliographic record

VenueGeophysical monograph · 2017
Typeother
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsRoyal Ontario MuseumWestern UniversityUniversity of Alberta
Fundersnot available
KeywordsBaddeleyiteBasaltPyroxeneMars Exploration ProgramMeteoriteGeologyMineral redox bufferMartianOlivineGeochemistryAstrobiologyChromiteIgneous rockFractional crystallization (geology)ChondriteCrystallizationMantle (geology)ChemistryZirconPhysics

Abstract

fetched live from OpenAlex

Baddeleyite (ZrO2) is an accessory mineral that occurs in variable abundances in planetary basaltic rocks, depending on melt compositions and crystallization conditions. Location and characterization of baddeleyite in a range of planetary basaltic rocks by both automated and manual electron microbeam methods reveals random distributions of grains exhibiting planar and sometimes concentric cathodoluminescent banding. Results from basaltic martian meteorites (shergottites) are emphasized, as their conditions of crystallization are representative of the broad range observed for other planetary basaltic rocks including lunar meteorites and the asteroidal eucrites. We find that baddeleyite forms from late-stage igneous melt in all of these planetary samples, associated with ferroan pyroxene and olivine, Fe-Ti oxides, sulfides, and phosphates, and that it is most common at higher oxygen fugacity (≥⃒ QFM). We conclude that the primary factors affecting baddeleyite occurrence are Zr concentrations in late-stage melts, SiO2 activity, and oxygen fugacity-dependent compatibilities of Zr in Fe-Ti oxides.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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 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

Citations15
Published2017
Admission routes1
Has abstractyes

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