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Record W2055543738 · doi:10.1117/12.850923

Review of high-speed fiber optic grating sensor systems

2010· article· en· W2055543738 on OpenAlexaff
Eric Udd, Jerry Benterou, Chadd May, Stephen J. Mihailov, Ping Lu

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsFiber Bragg gratingOptical fiberFiber optic sensorGratingComputer scienceMaterials scienceOpticsAcousticsVibrationOptoelectronicsTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Fiber grating sensors can be used to support a wide variety of high speed measurement applications. This includes measurements of vibrations on bridges, traffic monitoring on freeways, ultrasonic detection to support non-destructive tests on metal plates, and providing details of detonation events. This paper provides a brief overview of some of the techniques that have been used to support high speed measurements using fiber grating sensors over frequency ranges from 10s of kHz, to MHZ and finally toward frequencies approaching the GHz regime.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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 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

Citations24
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Fiber Optic SensorsFrench-language works237,207