MétaCan
Menu
Back to cohort
Record W1971601827 · doi:10.1364/ome.3.001742

Assembling an endcap to optical fibers by femtosecond laser welding and milling

2013· article· en· W1971601827 on OpenAlexaff
David Hélie, Samuel Gouin, Réal Vallée

Bibliographic record

VenueOptical Materials Express · 2013
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsGenia Photonics (Canada)
Fundersnot available
KeywordsMaterials scienceFemtosecondOptical fiberHard-clad silica optical fiberFiber laserCladding (metalworking)Fusion splicingOpticsWeldingLaser beam weldingLaserAll-silica fiberPlastic-clad silica fiberOptoelectronicsFiberComposite materialGraded-index fiberFiber optic sensor

Abstract

fetched live from OpenAlex

A novel method for assembling endcaps to optical fibers is presented. The method relies on femtosecond laser welding and milling of a glass slide to the polished end of the fiber. The fiber is welded to the glass slide in the cladding region so as to seal the core area without affecting its optical transparency. The same laser is used to mill through the glass slide thereby shaping a microscopic endcap with a diameter slightly larger than that of the fiber. The method was applied to both a standard and a microstructured optical fiber. Preliminary results are also presented on femtosecond laser welding parallel to an interface showing the potential of this approach for optical fiber fusion splicing.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.224
Teacher spread0.216 · 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

Citations28
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueOptical Materials ExpressSame topicLaser Material Processing TechniquesFrench-language works237,207