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Record W1654434542 · doi:10.1063/1.2718074

Comparison of the Structural Irregularity and Damage Evaluation Routine (SIDER) Inspection Method with Ultrasonic and Thermographic Inspections to Locate Impact Damage on an A320 Vertical Stabilizer

2007· article· en· W1654434542 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

VenueAIP conference proceedings · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Measurement and Detection Methods
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsNavyStiffnessNondestructive testingUltrasonic sensorImpact energyComputer scienceUltrasonic testingStructural engineeringForensic engineeringEngineeringAcoustics

Abstract

fetched live from OpenAlex

The U.S. Navy is currently involved in the development of several large area composite structures for fleet implementation. Techniques to provide rapid nondestructive inspection of large area composite structural components are required for these applications. An inspection technique, structural irregularity and damage evaluation routine (SIDER), has been developed by the Navy to rapidly locate areas of stiffness variation that results from processing anomalies and in‐service damage. SIDER was used to locate impact damage created on an A320 vertical stabilizer. Various impact energy levels were used, from 50 J, simulating barely visible impact damage, to 120 J, simulating significant impact damage. The SIDER results were compared with conventional ultrasonic and thermographic inspections.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.057
GPT teacher head0.368
Teacher spread0.312 · 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