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Record W4245254782 · doi:10.1364/cleo_si.2019.sf1j.3

Hexagonal boron nitride cavity optomechanics

2019· article· en· W4245254782 on OpenAlex
Prasoon K. Shandilya, Johannes E. Fröch, Matthew Mitchell, David P. Lake, Sejeong Kim, Milos Toth, Bishnupada Behera, Chris Healey, Igor Aharonovich, Paul E. Barclay

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

VenueConference on Lasers and Electro-Optics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOptomechanicsHexagonal boron nitrideSilicon nitrideMaterials scienceOptoelectronicsBoron nitrideSiliconNanotechnologySensitivity (control systems)BoronResonatorPhysicsElectronic engineeringGrapheneEngineering

Abstract

fetched live from OpenAlex

Hexagonal boron nitride (hBN) is an emerging layered material that plays a key role in a variety of 2D devices. Here, we demonstrate the first hBN cavity optomechanical system by integrating hBN nanobeams with silicon microdisk cavities. The system has 0.29 pm/ Hz sensitivity to hBN nanobeam motion.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score1.000

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)0.0010.000

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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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