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Record W3041184629 · doi:10.1007/s11661-020-05908-9

Advances in Microstructural Understanding of Wrought Aluminum Alloys

2020· article· en· W3041184629 on OpenAlex
J.D. Robson, Olaf Engler, Christophe Sigli, A. Deschamps, Warren J. Poole

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

VenueMetallurgical and Materials Transactions A · 2020
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of British Columbia
FundersEngineering and Physical Sciences Research Council
KeywordsMaterials scienceMicrostructureTexture (cosmology)AlloySynchrotronMetallurgyAluminiumPrecipitationCharacterization (materials science)Atom probeDeformation (meteorology)NanotechnologyComposite materialOpticsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Wrought aluminum alloys are an attractive option in the quest for lightweight, recyclable, structural materials. Modern wrought aluminum alloys depend on control of complex microstructures to obtain their properties. This requires an understanding of the coupling between alloy composition, processing, and microstructure. This paper summarizes recent work to understand microstructural evolution in such alloys, utilizing the advanced characterization techniques now available such as atom probe tomography, high-resolution electron microscopy, and synchrotron X-ray diffraction and scattering. New insights into precipitation processes, deformation behavior, and texture evolution are discussed. Recent progress in predicting microstructural evolution using computer modeling is also summarized.

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)0.000
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 score0.126
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.203
Teacher spread0.185 · 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