1.0 The Need for Reliability-Based Design
Bibliographic record
Abstract
There is a need to provide a design methodology for distribution and transmission poles that yields consistent reliabilities across all material types: wood, steel, concrete, fiberglass and other new materials. Prevailing US practice and most state laws require that transmission and distribution lines be designed, with a minimum, to meet requirements of recent editions of the National Electric Safety Code. (NESC, 2000) The NESC rules for the selection of design load and strength factors are largely based on successful experience, but they do not have a strong theoretical foundation. Some designers find the rules too restrictive, while others adopt more conservative criteria. In fact, individual utilities often develop their own loading agendas to complement the NESC rules. A desire to achieve more consistent reliabilities across materials was the impetus for the development of ASCE Manual 74 Guidelines for Transmission Line Structural Loading and the IEC. While Manual 74 offers consistent methods to calculate loads, there is still a need to provide consistent methods to calculate strength across pole materials.
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 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 | 0.027 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".