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Record W4320150404 · doi:10.1364/fio.2022.fw6c.2

Resolving sub-millisecond dynamics with single-pulse terahertz time-domain spectroscopy

2022· article· en· W4320150404 on OpenAlexaff
Nicolas Couture, Wei Cui, Markus Lippl, Rachel Ostic, Défi Junior Jubgang Fandio, Eeswar Kumar Yalavarthi, Aswin Vishnu Radhan, Angela Gamouras, Nicolas Y. Joly, Jean‐Michel Ménard

Bibliographic record

VenueFrontiers in Optics + Laser Science 2022 (FIO, LS) · 2022
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsNational Research Council CanadaMax Planck - University of Ottawa Centre for Extreme and Quantum PhotonicsUniversity of Ottawa
Fundersnot available
KeywordsMillisecondTerahertz radiationSpectroscopyTime domainPulse (music)Terahertz time-domain spectroscopyTerahertz spectroscopy and technologyMaterials sciencePhysicsOptoelectronicsOpticsComputer scienceDetectorAstronomy

Abstract

fetched live from OpenAlex

We present a system capable of single-pulse terahertz time-domain spectroscopy at an acquisition rate of 50 kHz. We demonstrate the capabilities of our system by monitoring sub-millisecond dynamics of carriers injected in Si.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.178
Teacher spread0.175 · 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.

Study designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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