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Record W2896326445 · doi:10.2351/1.5060371

Cutting of mullite-alumina ceramic plates with CO2 laser

2004· article· en· W2896326445 on OpenAlexaboutno aff
F. Quintero, J. Pou, F. Lusquiños, M. Boutinguiza, R. Soto, M. Pérez‐Amor, Florian Wagner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMulliteNozzleCeramicMaterials scienceSurface roughnessLaser cuttingWork (physics)Surface finishQuality (philosophy)LaserLaser beam machiningComposite materialMechanical engineeringMetallurgyOpticsLaser beamsEngineering

Abstract

fetched live from OpenAlex

In this work, a comprehensive analysis of the CO2 laser cutting of mullite-alumina ceramic plates is presented. The cut quality was assessed under the criterion of facilitate the comparison of the results obtained using different process parameters and two different assist gas injection systems. For this reason, some quantitative standard parameters were analyzed (kerf width, roughness, perpendicularity), besides of the preliminary survey of some features and the microscopic examination of the heat affected zone. The results demonstrate the improvement of the cut quality using an assist gas injection system based on an off-axis De Laval nozzle.

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 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 score0.188
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.005
GPT teacher head0.189
Teacher spread0.184 · 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
Published2004
Admission routes1
Has abstractyes

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