MétaCan
Menu
Back to cohort
Record W2466994864 · doi:10.5539/jmsr.v5n3p66

Development of Electrically Assisted Rapid Heating for Metal Forming of Hot-Stamping Process

2016· article· en· W2466994864 on OpenAlexvenueno aff
Mahmudun Nabi Chowdhury, Dinh Thi Kieu Anh

Bibliographic record

VenueJournal of Materials Science Research · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceClampingHot stampingElectrodeElectric heatingComposite materialHeating elementCurrent (fluid)Electric currentInduction heatingJoule heatingStampingContact resistanceMetallurgyMechanical engineeringElectrical engineeringElectromagnetic coil

Abstract

fetched live from OpenAlex

<p class="1Body">Two different concepts of electrically assisted (EA) rapid heating of Al–Si coated hot-stamping steels are compared. In “along the surface” EA heating (or simply EA surface heating), the electric current is simply applied to a specimen by clamping the each end of the specimen length with a set of flat rectangular electrodes. In “through the thickness” EA heating (or simply EA thickness heating), the electric current is applied to a specimen by attaching a set of electrodes with multiple contact points on upper and lower surfaces of the specimen. While the EA surface heating generally requires a shorter heating time due to a higher electrical resistance in the length direction, the EA thickness heating also may provide a technical advantage that the heating area can be more easily configured in a case of partial austenization.</p>

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 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)0.006
metaresearch head score (Gemma)0.001
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 score0.043
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 science0.0010.000
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 head0.083
GPT teacher head0.356
Teacher spread0.273 · 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 teacher head, 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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials Science ResearchSame topicMicrostructure and Mechanical Properties of SteelsFrench-language works237,207