Bibliographic record
Abstract
Very often highway departments drive test piles at proposed bridge locations to refusal or to a predetermined set and utilize these records to determine the pile capacity using the Hiley and Engineering News Record pile driving formulae. This test pile driving also provides information on the depth to which the piles can be driven and on problems that may likely be encountered during production piling. The pile capacity obtained from pile driving formulae is generally used by the structural engineer to undertake the preliminary design of the bridge foundations. The use of the pile driving approach to capacity determination often works well when the ground is competent at relatively shallow depths. However, where piles cannot achieve refusal unless driven into stiff or hard ground a geotechnical evaluation of pile capacity becomes more relevant and is often relied upon for pile capacity determination. This paper describes a site where H-pile and closed end pipe piles attained refusal at a depth of 31 metres in hard clay till and where the geotechnical evaluation recommended that the pier piles be terminated at a higher elevation. To demonstrate that the geotechnical recommendations were acceptable, static load testing and Pile Driving Analyzer tests were undertaken. The detailed testing program demonstrated that the driving of piles to refusal was not necessary to achieve the desired pile capacities and that conventional static analysis provided capacities that were sufficiently reliable for design.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".