MétaCan
Menu
Back to cohort

Asymmetric Incremental Sheet Forming

2005· article· en· W2016460685 on OpenAlexaff
J. Jeswiet

Bibliographic record

VenueAdvanced materials research · 2005
Typearticle
Languageen
FieldEngineering
TopicLaser and Thermal Forming Techniques
Canadian institutionsQueen's University
FundersAtsumi International Scholarship Foundation
KeywordsSheet metalIncremental sheet formingForming processesMetal formingSpinningMaterials scienceDeformation (meteorology)Mechanical engineeringShear (geology)Engineering drawingManufacturing engineeringEngineeringMetallurgyComposite material

Abstract

fetched live from OpenAlex

The use of computers in manufacturing has enabled the development of several new sheet metal forming processes. This paper describes modifications that have been made to traditional forming methods such as conventional spinning and shear forming, where deformation is localized. Recent advances have enabled this localized deformation to be accurately controlled and studied. Current developments have been focused on forming asymmetric parts using CNC technology, without the need for costly dies. Asymmetric Incremental Forming has the potential to revolutionize sheet metal forming, making it accessible to all levels of 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.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.340
Teacher spread0.308 · 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

Citations41
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced materials researchSame topicLaser and Thermal Forming TechniquesFrench-language works237,207