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Record W2913818124 · doi:10.7567/1347-4065/aafb50

Ring resonator designed for biosensing applications manufactured on 300 mm SOI in an industrial environment

2019· article· en· W2913818124 on OpenAlexaff
Michele Calvo, Sylvain Guerber, Guillaume Beaudin, Michael Canva, Charles Baudot, F. Bœuf, Paul G. Charette

Bibliographic record

VenueJapanese Journal of Applied Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsSilicon on insulatorResonatorBiosensorMaterials scienceOptoelectronicsNanotechnologyRing (chemistry)ChemistrySilicon

Abstract

fetched live from OpenAlex

Abstract This paper reports on the design and characterization of a silicon nitride ring resonator-based device for biosensing manufactured with the STMicroelectronics 300 mm R&D Datacom Advanced PHotonic Nanoscale Environment (DAPHNE) industrial platform. The experimental results demonstrate a 300 nm/RIU bulk sensitivity and a 0.125 nm resonant peak shift per nanometer of biological adlayer thickness change. These results, comparable to the state of the art in ring resonator-based biosensors, demonstrate the potential of the DAPHNE industrial platform for manufacturing high-performance photonics biosensors at low cost.

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 score0.260
Threshold uncertainty score0.479

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 head0.019
GPT teacher head0.226
Teacher spread0.207 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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