MétaCan
Menu
Back to cohort
Record W2984342347 · doi:10.1063/1.5113624

An ultra-stable 2.9 μm guided-wave chip laser and application to nano-spectroscopy

2019· article· en· W2984342347 on OpenAlex
David G. Lancaster, Dale E. Otten, Adrian Cernescu, G. Y. Chen, Claes Johnson, Tanya M. Monro, Jérôme Genest

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAPL Photonics · 2019
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversité Laval
FundersAustralian Research Council
KeywordsLaserMaterials scienceOpticsLaser power scalingContinuous waveFar-infrared laserSpectroscopyOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

We present a configurable guided-wave planar glass-chip laser that produces low-noise and high-quality continuous-wave laser emission tunable from 2.82 to 2.95 µm. The laser has a low threshold and intrinsic power and mode stability attributable to the high overlap of gain volume and pump mode defined by an ultrafast laser inscribed waveguide. The laser emission is single transverse-mode with a Gaussian spatial profile and M2x,y ∼ 1.05, 1.10. The power drift is ∼0.08% rms over ∼2 h. When configured in a spectrally free-running cavity, the guided-wave laser emits up to 170 mW. The benefit of low-noise and stable wavelength emission of this hydroxide resonant laser is demonstrated by acquiring high signal-to-noise images and spectroscopy of a corroded copper surface film with corrosion products containing water and hydroxide ions with a scattering-scanning near-field optical microscope.

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.

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 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 score0.261
Threshold uncertainty score0.694

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 head0.226
Teacher spread0.219 · 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