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Record W2768550880 · doi:10.3390/ijgi6120382

Recent Advances of Structures Monitoring and Evaluation Using GPS-Time Series Monitoring Systems: A Review

2017· review· en· W2768550880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueISPRS International Journal of Geo-Information · 2017
Typereview
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsUniversité Laval
FundersMinistry of Land, Infrastructure and TransportIncheon National University
KeywordsGlobal Positioning SystemComputer scienceStructural health monitoringReal-time computingIdentification (biology)Series (stratigraphy)Precise Point PositioningEngineeringTelecommunicationsGNSS applicationsGeology

Abstract

fetched live from OpenAlex

This paper presents the recent development in Structural Health Monitoring (SHM) applications for monitoring the dynamic behavior of structures using the Global Positioning Systems (GPS) technique. GPS monitoring systems for real-time kinematic (RTK), precise point positioning (PPP) and the sampling frequency development of GPS measurements are summarized for time series analysis. Recent proposed time series GPS monitoring systems, errors sources and mitigation, as well as system analysis and identification, are presented and discussed.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.005
Open science0.0010.000
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 head0.078
GPT teacher head0.428
Teacher spread0.350 · 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