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Record W4392240896 · doi:10.1364/ol.515199

Fast rate dual-comb spectrometer in the water-transparent 7.5–11.5 µm region

2024· article· en· W4392240896 on OpenAlexaff
Luca Moretti, Mathieu Walsh, Nawaf Abualsaud, Davide Gatti, Marco Lamperti, Jérôme Genest, Aamir Farooq, Marco Marangoni

Bibliographic record

VenueOptics Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsUniversité Laval
FundersHORIZON EUROPE European Innovation CouncilClean Combustion Research Center, King Abdullah University of Science and Technology
KeywordsSpectrometerDetectorOpticsMaterials scienceSpectral resolutionTerahertz radiationBandwidth (computing)Water vaporPhase noiseOptoelectronicsPhysicsSpectral line

Abstract

fetched live from OpenAlex

We introduce a dual-comb spectrometer based on erbium fiber oscillators at 250 MHz that operates in the 7.5–11.5 µm spectral range over optical bandwidths up to 9 THz with a multi-kHz acquisition rate. Over an observation bandwidth of 0.8 THz, the signal-to-noise ratio per spectral point reaches 168 Hz 0.5 at an acquisition rate of 26 kHz, which allows the investigation of transient processes in the gas phase at high temporal resolution. The system also represents an attractive solution for multi-species atmospheric gas detection in open paths due to the water transparency of the spectral window, the use of thermo-electrically cooled detectors, and the out-of-loop phase correction of the interferograms.

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 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 score0.195
Threshold uncertainty score0.399

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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 teacher head, 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

Citations8
Published2024
Admission routes1
Has abstractyes

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