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Record W4380203470 · doi:10.31399/asm.amp.2018-04.p016

Overcoming Barriers to Magnesium Rolling

2018· article· en· W4380203470 on OpenAlexaff
A. Javaid, Mark Kozdras, Frank Czerwiński

Bibliographic record

VenueAM&P Technical Articles · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsFormabilityMagnesiumMaterials scienceMetallurgyObstacleScale (ratio)Mechanical engineeringManufacturing engineeringEngineeringPhysicsPolitical science

Abstract

fetched live from OpenAlex

Abstract The key obstacle to industrial scale magnesium rolling is the element’s inherently poor formability at room temperature. To address this challenge, the search is on for new magnesium alloys that feature improved formability along with novel rolling techniques. This article describes R&D activities at CanmetMaterials aimed at expanding manufacturing capabilities of magnesium-based sheet materials for future applications in transport vehicles.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.004

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 head0.017
GPT teacher head0.254
Teacher spread0.238 · 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 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

Citations7
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAM&P Technical ArticlesSame topicMagnesium Alloys: Properties and ApplicationsFrench-language works237,207