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Record W4293221358 · doi:10.3390/met12091401

Critical Evaluation and Thermodynamic Optimization of the Cu-Zn, Cu-Se and Zn-Se Binary Systems

2022· article· en· W4293221358 on OpenAlex
Yu Tang, Jie Ma, Dong Han, Jian Wang, Haiying Qi, Liling Jin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMetals · 2022
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsPolytechnique Montréal
FundersNatural Science Foundation of Anhui Province
KeywordsIntermetallicBinary numberThermodynamicsGibbs free energyZincPhase diagramMaterials scienceCopperCrystal structureBinary systemFormalism (music)Phase (matter)ChemistryCrystallographyMetallurgyPhysicsMathematicsOrganic chemistry

Abstract

fetched live from OpenAlex

In our study, a complete review of the literature, critical evaluation and thermodynamic assessment of the Cu-Zn, Cu-Se and Zn-Se binary systems were carried out. The modified quasi-chemical model (MQM) was applied to describe the Gibbs energy of the liquid phase. The Gibbs energies of all intermetallic compounds and terminal solid solutions were described using the compound energy formalism (CEF) model. The re-optimization of the Cu-Zn binary system was carried out by considering the ordered bcc_B2 crystal structure of the β’ phase. Moreover, the β and δ phases in the Cu-Zn binary system with the same bcc_A2 crystal structure were modeled as one single phase in the present work. A self-consistent thermodynamic database was constructed for the Cu-Zn, Cu-Se and Zn-Se binary systems, work that formed part of a comprehensive thermodynamic database development project researching zinc-based biodegradable materials.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.217

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 communication0.0000.000
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 head0.032
GPT teacher head0.292
Teacher spread0.260 · 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