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Record W4405363193 · doi:10.1117/12.3047826

2.8 μm gain-switched erbium-doped fluoride fiber laser pumped at 1.7 μm

2024· article· en· W4405363193 on OpenAlexaff
Yang Xiao, Yuxuan He, Yewei Shen, Tiantian Yin, Wentao Liang, Xusheng Xiao, Haitao Guo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSolid State Laser Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsFiber laserMaterials scienceErbiumLaserFluorideOptoelectronicsDopingErbium doped fiber amplifierOpticsFiberOptical amplifierChemistryPhysicsWavelengthInorganic chemistry

Abstract

fetched live from OpenAlex

Gain-switched mid-infrared 1 and 7 mol. % erbium-doped fluoride fiber lasers pumped at 1.7 μm were demonstrated. They delivered 2.8 μm pulsed laser with maximum average powers of 306 mW and 390 mW, respectively, corresponding to recorded laser efficiencies of 43.6% and 35.5%. This work exhibits the potential of the 1.7 μm pulsed pumping scheme for gain-switched 2.8 μm erbium-doped fluoride fiber lasers and this pumping scheme paves the way for high-efficient pulsed fiber lasers in the 3 μm region.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.224
Teacher spread0.213 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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