Review of non-destructive testing for quality evaluation of in-service timber utility poles
Bibliographic record
Abstract
Wooden utility poles are widely utilized in power distribution and telecommunication infrastructure across North America. Exposure to weather, fungal decay , and termite infestations accelerate the degradation of wooden poles, leading to strength loss which may cause low reliability of power distribution. Routine inspections are conducted for condition assessment, enabling the identification of potential defects, and facilitating timely planning for renewals. The reliability and accuracy of these assessment techniques are important to illustrate the real condition of the poles. Incorrect assessments of pole strength can cause major problems, either poles are replaced too early due to mistakenly identified defects, or they fail because real issues were not timely identified. This paper aims to present a comprehensive review of various condition assessment techniques for in-service timber poles. It covers conventional inspection methods, important parameters indicating the strength of utility poles, and non-destructive testing (NDT) methods. The effectiveness of these techniques is analyzed, highlighting their respective benefits and limitations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".