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Record W4393976359 · doi:10.1002/9781119678892.ch9

APPLICATIONS AND DEVELOPMENT OF THE SAGNAC INTERFEROMETER

2024· other· en· W4393976359 on OpenAlexaff
Eric Udd

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicGeophysics and Sensor Technology
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsInterferometrySagnac effectPhysicsOpticsComputer science

Abstract

fetched live from OpenAlex

Fiber optic gyro development directed toward aerospace applications began shortly after the first viable, low-loss optical fibers were fabricated in the mid-1970s. Initial developments included the demonstration of the first open- and closed-loop fiber optic gyros in 1976 and 1978. The range and depth of fiber optic sensor technology continued to expand rapidly from the 1990s to the present with advancements in a wide range of fiber optic sensor types and applications enabled in part by advancements in the telecommunication industry. The Sagnac interferometer responds to a wide variety of environmental effects that must be addressed to increase performance and reduce errors of the fiber optic gyroscope. These investigations open the opportunity for new applications of the Sagnac interferometer. The use of an integrated optical circuit and polarization-preserving optical fiber to support the closed-loop fiber gyro enabled the prospect of significant manufacturing savings and better performance than other earlier approaches.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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