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Towards Ultra-Fast Femtosecond-Laser-Assisted Chemical Etching of Mid-IR Transmitting Barium Germano-Gallate (BGG) Glass

2025· article· en· W4413462177 on OpenAlexaff
Yann Serre, Théo Guérineau, Fouad Alassani, Jérôme Lapointe, Réal Vallée, Lionel Canioni

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsGenia Photonics (Canada)
Fundersnot available
KeywordsFemtosecondBariumMaterials scienceGallateEtching (microfabrication)LaserOptoelectronicsGermanium compoundsOpticsNanotechnologyGermaniumSiliconChemistryMetallurgyNuclear chemistryPhysics

Abstract

fetched live from OpenAlex

The development of very-high-intensity femtosecond laser pulses in the 1980s has led to significant advancements in the field of laser micro/nanostructuring of materials [1]. The Direct Laser Writing (DLW) process, which involves creating 3D structures by focusing a laser beam within transparent materials, stands apart from UV photolithography due to its ability to shape complex three-dimensional geometries. However, the high surface roughness associated with this process prevents the achievement of optical-quality inscriptions.

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)
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 score0.098
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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