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Record W3127189074 · doi:10.2749/vancouver.2017.1469

Distributed Deflection Measurement of Reinforced Concrete Elements Using Fibre Optic Sensors

2017· article· en· W3127189074 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

VenueReport · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsQueen's University
Fundersnot available
KeywordsDeflection (physics)Structural engineeringStiffnessReinforced concreteBendingDisplacement (psychology)TransducerEnvironmental scienceEngineeringOpticsPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

<p>The construction of new infrastructure required to meet the demands of a growing global population has substantial negative impacts on the environment. Structural engineers can help reduce these negative impacts through efficient material use in reinforced concrete (RC) design, as steel and concrete production accounts for a significant portion of global greenhouse gas emissions. In RC design, stiffness and support condition assumptions often lead to large discrepancies between design models and true behaviour. Critical insight would be captured if the deflected shape of RC beams could be practically measured. A method of measuring the deflected shape of RC beams using distributed fibre optic sensors (FOS) is presented. Six RC beams were tested in three-point bending. The FOS results were evaluated against displacement transducers and were found to capture deflected shapes accurately until loading exceeded 50% of the beams’ ultimate capacities.</p>

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.642

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 head0.041
GPT teacher head0.283
Teacher spread0.242 · 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