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Development of Digital Quasi-embossing Technology with an Inkjet Printer-2

2013· article· en· W4378376703 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTechnical programs and proceedings/Technical program and proceedings · 2013
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsEmbossingStampingInkwellFOIL methodDigital printingPressingMaterials scienceInkjet printing3d printerComputer scienceEngineering drawingMechanical engineeringComposite materialEngineeringMetallurgy

Abstract

fetched live from OpenAlex

Conventional embossing printing technology which can be used to produce metallic glossy images on stereo-shaped objects needs a pressing plate with the image patterns specially arranged. Accordingly, the embossing system is relatively expensive and lacks the adaptability for high-mix low-volume production. Considering these facts, we developed the Digital Quasiembossing Technology (DQT) which consisted of the technology combined with UV-curable inkjet printing and hot foil-stamping. We reported the DQT for the first time at NIP 28 in Quebec City last year. This paper is a continuation of the last report and describes the following facts. (a) We have improved the adhesion of UV-curable ink to a metallic foil, and consequently we can make not only relatively small-sized products but also large-sized ones with pictures and letters printed thereon. (b) The improved DQT system can produce higher gloss than the last system reported at NIP 28.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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