MétaCan
Menu
Back to cohort
Record W2089814259 · doi:10.1117/12.2075051

Silicon photonics characterization platform for gyroscopic devices

2014· article· en· W2089814259 on OpenAlexafffund
Miguel Ángel Guillén-Torres, Maan Almarghalani, Élie Sarraf, Michael Caverley, Nicolas A. F. Jaeger, Edmond Cretu, Lukas Chrostowski

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCMC MicrosystemsUniversity of Washington
KeywordsGyroscopeSilicon on insulatorBandwidth (computing)ResonatorPhotonicsMicroelectromechanical systemsMaterials scienceOptical ring resonatorsPayload (computing)Rotation (mathematics)Silicon photonicsOptoelectronicsElectronic engineeringSiliconOpticsComputer sciencePhysicsEngineeringTelecommunicationsAerospace engineeringNetwork packet

Abstract

fetched live from OpenAlex

Large-area silicon-on-insulator (SOI) ring resonators, to be used as optical gyroscopes, have been designed and fabricated using an e-beam process. To characterize the devices, an automated turntable stage with an embedded high resolution gyroscope has been built. Its large payload capacity allows for safe rotation of a temperature-controlled opto-mechanical setup. A field programmable gate array interface has been implemented for mechanical actuation and signal acquisition. Various rotation schemes have been implemented to characterize the apparatus and devices. The turntable exhibits a bandwidth of 0.54 Hz, and minimum and maximum repeatable angular rates of 27 and 74.3 degrees per second (dps), with a maximum associated angular rate noise level of 2 dps.

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)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.219
Teacher spread0.209 · 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

Citations6
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicPhotonic and Optical DevicesFrench-language works237,207