MétaCan
Menu
Back to cohort
Record W3110756163 · doi:10.1016/j.jma.2020.10.003

Progress in twin roll casting of magnesium alloys: A review

2020· review· en· W3110756163 on OpenAlex
A. Javaid, Frank Czerwiński

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Magnesium and Alloys · 2020
Typereview
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsNatural Resources Canada
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsCastingMaterials scienceMetallurgyMagnesium alloyMagnesiumMicrostructureManufacturing engineeringMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Twin roll casting was commercialized for a strip production from ferrous and non-ferrous alloys in the 1950s; however, its application to magnesium has proven difficult and still creates major challenges. This report describes global efforts in expanding manufacturing capabilities of magnesium sheet through twin roll casting path, offering many benefits, including a reduction in number of processing steps and energy savings. In addition to hardware design, alloy transformation during processing, product microstructure and properties, examples of successful solutions along with present technology and knowledge limitations are discussed. A particular attention is paid to developments at CanmetMATERIALS, having the only in North America pilot scale twin roll casting facility, devoted to magnesium. Efforts are described that aim at design of new magnesium alloys, which could take advantage of unique processing conditions during twin roll casting and contribute to the overall progress in magnesium sheet manufacturing.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.309
Teacher spread0.269 · 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