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Record W6898737077 · doi:10.57760/sciencedb.12874

Data for: Shock Metamorphic Effects in Feldspar in Martian Regolith Breccia: Measurement, Quantification, and Implications

2024· dataset· en· W6898737077 on OpenAlexaff

Bibliographic record

VenueScienceDB · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of TorontoRoyal Ontario MuseumWestern University
Fundersnot available
KeywordsRegolithPlagioclaseFeldsparMartianBrecciaAlkali feldsparMeteoriteClastic rock

Abstract

fetched live from OpenAlex

This dataset supports the study "Shock Metamorphic Effects in Feldspar in Martian Regolith Breccia: Measurement, Quantification, and Implications." It includes data from various Martian regolith breccia samples, including NWA 7034_A and B, 7034_small_01A, 7034_small_01_thin, 7034_small_02A, 7034_small_02B, 7034_small_03, NWA 7475, NWA 8171_small, 8171_medium, 8171_big, and NWA 11220. The dataset is organized as follows:Spreadsheets (S1-S3):Spreadsheet S1 contains the analyzed results of micro-XRD for 149 plagioclase clasts and Raman data for 35 clasts examined in these meteorites. This spreadsheet includes the Full Width at Half Maximum (FWHMχ) values averaged along the χ direction (Debye rings) obtained from 2D XRD images for each analyzed target. Additionally, it provides the statistical information derived from these analyses. Furthermore, 35 of these 149 clasts were analyzed using Raman spectroscopy, and their relative intensities for characteristic Raman bands at ~478 cm⁻¹ and 508 cm⁻¹ are presented.Spreadsheet S2 presents the analyzed micro-XRD data for 21 alkali feldspar grains in these meteorites. Similar to S1, Spreadsheet S2 includes the averaged FWHMχ for each analyzed alkali feldspar target, along with the corresponding statistical information.Spreadsheet S3 provides the EPMA data for feldspar minerals in NWA 8171_small and NWA 8171_medium. These data correspond to Fig. S2a.Raw Data (10 folders for micro-XRD and 1 folder for Raman):Micro-XRD folders: Each folder corresponds to one Martian regolith breccia meteorite and contains the raw micro-XRD data of each analyzed plagioclase grain. The raw data is provided in two .gfrm files, representing two frames of 2D XRD images. Bruker EVA software was used to process the 2D XRD images. Full Width at Half Maximum (FWHM) values along the χ direction (Debye rings) can be obtained from these 2D XRD images for each analyzed target. Additionally, the data can be integrated into a conventional 1D XRD pattern plotting intensity versus 2θ angles for phase identification.Raman folder: This folder contains Raman data for the 35 plagioclase clasts examined in the study. The data is provided in .txt files, which were processed using Renishaw’s Raman WiRE™ software (www.renishaw.com/wire) to acquire the relative intensities for characteristic Raman bands at ~478 cm⁻¹ and 508 cm⁻¹.FWHMχ Measurement:The .gfrm files are used for peak width measurements along the Debye ring dimension (χ direction). As explained in methods section 2.2 in the manuscript, the intensity of diffracted X-rays as a function of the χ angle (i.e., along the Debye ring) is used for strain analysis. The analysis process is as follows:2D XRD images are integrated along the χ dimension using Bruker EVA software to obtain the intensity distribution corresponding to individual lattice reflections.The Full Width at Half Maximum (FWHMχ) of the resulting peak along the χ dimension is determined using Renishaw WiRE software. Multi-curve fitting is necessary for integrated X-ray distributions revealing multiple peaks (see Fig. 1).Finally, the cumulative FWHMχ values (ΣFWHMχ) are calculated to quantitatively characterize the shock level in each plagioclase grain.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.072
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0720.052

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 head0.142
GPT teacher head0.365
Teacher spread0.223 · 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 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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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