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Record W7048396393

Laser beam melting drives efficiency of tooling applications: Presentation held at Canada Makes Additive Manufacturing Forum - Aerospace and Automotive Tooling, October 24, 2018, Waterloo

2018· other· en· W7048396393 on OpenAlexaboutno aff

Bibliographic record

VenueFraunhofer-Publica (Fraunhofer-Gesellschaft) · 2018
Typeother
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsnot available
Fundersnot available
KeywordsAerospaceAutomotive industryFusible alloyAerospace materialsCastingLaser beamsSheet metalStampingDie (integrated circuit)
DOInot available

Abstract

fetched live from OpenAlex

The additive Laser Beam Melting (LBM) makes it possible – by processing conventional metallic materials such as tool steel – to manufacture innovative tools and molds. The almost limitless freedom of design of LBM enables innovative elements and complex functional structures and thus has the potential to change toolmaking. Plastic injection molding, light metal die casting but also metal forming such as stamping and press hardening (hot sheet metal forming) can benefit greatly from additive manufactured tooling. The presentation provides an overview of the state of the art with application examples such as the thermal management of forming tools and shows the development path for the near future.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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