MétaCan
Menu
Back to cohort
Record W3135048613 · doi:10.1007/s00410-020-01771-4

A new activity model for Fe–Mg–Al biotites: II—Applications in the K2O–FeO–MgO–Al2O3–SiO2–H2O (KFMASH) system

2021· article· en· W3135048613 on OpenAlexaff
Edgar Dachs, Stan Roozen, Artur Benisek

Bibliographic record

VenueContributions to Mineralogy and Petrology · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsMcGill University
FundersAustrian Science Fund
KeywordsBiotiteOctahedronMineralogyMineralChemistryThermodynamicsCrystallographyAnalytical Chemistry (journal)GeologyMaterials scienceMetallurgyCrystal structurePhysicsQuartz

Abstract

fetched live from OpenAlex

Abstract The new biotite activity model and standard-state thermodynamic properties of Ann, Phl, and Eas presented in part-I were used to make pseudosections of bulk compositions representing experimental Fe–Mg exchange equilibria and (model) pelitic bulk rock compositions in the system K2O–FeO–MgO–Al2O3–SiO2–H2O (KFMASH), using mainly the software Perple_X. These pseudosection calculations (termed ‘our calculation(s)’ in the following) were compared to analogous ones performed with the solution model of biotite and thermodynamic data cited in White et al. (J Metamorph Geol 32:261–286, 2014, 10.1111/jmg.12071), termed ‘W14 calculation’. Our calculations with the experimental bulk composition used by Zhou (Ti–Mg–Fe biotites: formation, substitution, and thermodynamic properties at 650 to 900 °C and 1.1 Kb with fO2 defined by the CH4–graphite buffer. PhD thesis, State University of New York, 1994) in his experimental study of the Fe–Mg exchange between biotite (Bt) and olivine (Ol) confirm that biotite had no or only minimal octahedral Al (AlVI) in these experiments. The experimental data of Ferry and Spear (—FS78, Contrib Mineral Petrol 66:113–117, 1978, 10.1007/BF00372150) on the Fe–Mg distribution between biotite and garnet (Grt) are well reproduced by our calculations. The computed composition of biotite (XFe) in equilibrium with garnet of Alm90Py10 composition and the resulting lnKD values as a function of temperature are in good agreement with the experimental brackets. An analogous W14 calculation on the same Fe-rich bulk composition predicts too high XFeBt in order of 0.1 mol fraction. The AlVI contents of biotite of about 0.3–0.45 apfu, as measured by Gessman et al. (Am Mineral 82:1225–1240, 1997, 10.2138/am-1997-11-1218) in similar biotite–garnet exchange experiments performed with Alm80Py20 and Alm70Py30 garnets, are well reproduced by our, as well as by W14 calculations. The extent of Tschermak substitution in biotite in the FS78 experiments, which had Fe-richer bulk compositions, has not been measured. Comparing the FS78 biotites with the ones from Gessman et al. (Am Mineral 82:1225–1240, 1997, 10.2138/am-1997-11-1218), it is very likely that the biotites reported in FS78 contained AlVI in the same order of ca. 0.3–0.4 apfu. A T–XFe (= molar FeO/(FeO + MgO) pseudosection demonstrates the bulk composition dependence of lnKD of the Mg/FeGrt/Bt exchange reaction in high-variance fields. Further comparisons, demonstrating the application of the new biotite solution model in the KFMASH system, are presented in pseudosections constructed for an average model pelite, as well as for a natural high-T/low-P and a natural high-P metapelite. The pseudosections show that biotite according to our biotite model breaks down at lower temperatures and pressures than predicted from the W14 biotite model in the KFMASH system. This means that KFMASH biotite can break down before the wet solidus is reached, which can explain the existence of dry high-T/low-P metapelites. At higher pressures, biotite according to our calculations breaks down at lower pressures than computed with the W14 biotite model. Before biotite breaks down, however, its AlVI content based on our calculations could potentially be used for pseudosection barometry, similarly as the Si-in-phengite barometer. These trends need to be confirmed by a future extension of our model which incorporates Ti, Fe3+ and a di–tri-octahedral substitution.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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 designTheoretical or conceptual
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueContributions to Mineralogy and PetrologySame topicGeological and Geochemical AnalysisFrench-language works237,207