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Record W4240159407 · doi:10.1109/imtc.1991.161566

GaAs-based fiber optic pressure sensor

2002· article· en· W4240159407 on OpenAlexaff
W.J. Bock, M. Beaulieu, A.W. Domanski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsPressure sensorMaterials scienceHydrostatic pressureSIGNAL (programming language)Optical fiberOptoelectronicsFiber optic sensorMulti-mode optical fiberDisplacement (psychology)Dynamic rangeOpticsPhysicsComputer science

Abstract

fetched live from OpenAlex

A description is given of a sensor developed for measurement of hydrostatic pressure up to at least 100 MPa at a standard range of ambient temperatures. The sensor exploits the displacement of the optical absorption edge occurring in semiconductors under the influence of hydrostatic stress as a result of pressure-induced energy shifting of conduction band extrema. The sensing element is composed of an intrinsically pure GaAs single crystal configured in the form of a microprism located at the sensor tip, and attached to two multimode (50/125 mu m) optical fibers designed to deliver input light to the sensor and to output a pressure-modulated light signal to the outside of a pressure region. Characterization of the sensor has been performed for pressures up to 100 MPa and for temperatures ranging from 273 to 330 K. A procedure is proposed involving the use of two (active and compensating) sensors to minimize temperature drift through appropriate analog signal processing or, alternatively, through digital computations.>

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)0.000
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.206
Teacher spread0.192 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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