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Record W2922012168 · doi:10.1117/12.2509945

Dual-wavelength, cascaded cavities bismuth-doped fiber laser in 1.7 μm wavelength range

2019· article· en· W2922012168 on OpenAlexaff
Galina Nemova, Jinghao Qiao, Lawrence R. Chen, Sergei Firstov, E. M. Dianov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsMcGill University
Fundersnot available
KeywordsOpticsLaserWavelengthMaterials scienceFiber laserCascadeFiber Bragg gratingDispersion-shifted fiberBismuthDistributed feedback laserOptoelectronicsOptical fiberPhysicsFiber optic sensorChemistry

Abstract

fetched live from OpenAlex

A comprehensive theoretical investigation of a dual wavelength, cascade cavity bismuth-doped fiber (BDF) laser operating in the wavelength range of 1.7μm is presented. The fiber laser model is based on parameters extracted from experimental characterization of the BDF. The BDF serves as an active medium with optical gain in the wavelength region from 1.65μm to 1.8μm. The laser cavity is defined by a 90% mirror on one end of the BDF and two fiber Bragg gratings (FBG1 and FBG2) separated with the BDF on the other end of the laser cavity. One of the gratings FBG1 with the peak reflectivity 95% is centered at 1.725μm. The second one FBG2 with peak reflectivity of 90% is centered at 1.729μm. Both FBGs have a 3-dB bandwidth of ~0.5nm. It is shown that the cascade laser can operate at two 1.725μm and 1.729μm wavelengths with different powers depending on the parameters of the structure.

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 score0.006

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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
Published2019
Admission routes1
Has abstractyes

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