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Record W4389565597 · doi:10.3390/min13121531

Innovative Structural Characterization of Natural Villiaumite Crystal

2023· article· en· W4389565597 on OpenAlexaboutno aff
Katarzyna Chruszcz‐Lipska, Elżbieta Szostak, Krzysztof Zborowski

Bibliographic record

VenueMinerals · 2023
Typearticle
Languageen
FieldMaterials Science
TopicCrystal Structures and Properties
Canadian institutionsnot available
FundersAcademic Computer Centre Cyfronet, AGH University of Science and TechnologyInfrastruktura PL-GridAkademia Górniczo-Hutnicza im. Stanislawa Staszica
KeywordsNatural mineralMuffle furnaceInfraredOrange (colour)MineralKola peninsulaInfrared spectroscopyMineralogyAnalytical Chemistry (journal)Crystal structureChemical compositionMaterials scienceChemistryEnvironmental chemistryMetallurgyCrystallographyGeologyGeochemistryPhysicsOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

The work presents the latest scientific research on the far infrared spectrum of the natural mineral villiaumite (chemical formula NaF). The three samples of villiaumite examined came from the Khibiny Mountains in the Kola Peninsula (Russia) and from Mon Saint Hilaire in Quebec (Canada). The tested villiaumite samples began to change color very slowly after being heated above 300 °C in a muffle furnace. Subsequent color changes required heating at increasingly higher temperatures for approximately 48–72 h. Samples of the reddish mineral villiaumite turned orange, pink and finally colorless (at approximately at 430 °C). Because the color of villiaumite changes under the influence of temperature, far infrared spectra were measured for the samples at room temperature and for the sample heated to 100, 200, 300, 400 and 500 °C. Additionally, using density functional theory (DFT/B3LYP/6-31+g*), the spectrum of NaF (125-atom model of crystal structure) was simulated for the first time and compared with the experimental spectrum of pure sodium fluoride (a chemical reagent) and the mineral villiaumite.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.036
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.249
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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

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