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Record W3125741471 · doi:10.1364/assl.2020.jtu5a.5

Power Scaling of Single-mode Erbium-doped Alumino-phosphosilicate Fiber Lasers

2020· article· en· W3125741471 on OpenAlexaff
Louis-Charles Michaud, Lauris Talbot, Frédéric Gauvin, Vincent Boulanger, Marc-Antoine Boulé, Romain Dubroeucq, Simon Dubuis, Albert Dupont, Anna Gagné-Landmann, Charles Matte-Breton, Antoine Séverin Ollier, Nicolas Grégoire, Steeve Morency, Younès Messaddeq, Martin Bernier

Bibliographic record

VenueLaser Congress 2020 (ASSL, LAC) · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceFiber laserLaser power scalingYtterbiumOptoelectronicsErbiumDopingLaserPower (physics)ScalingOpticsPhysics

Abstract

fetched live from OpenAlex

We report the highest power achieved to our knowledge for an ytterbium-free alumino-phosphosilicate co-doped erbium fiber laser with 51W of output power. We will also discuss on the 100W-level power scaling potential of such laser.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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