Lateral Performance of Large-Capacity Helical Piles
Bibliographic record
Abstract
The lateral performance of large-capacity helical piles is of significant interest because they can offer an efficient alternative to conventional piling systems in many applications. This paper presents the results of two field lateral load tests conducted on 6.0 m and 9.0 m large-capacity helical piles installed in cohesive soil. The test piles were close-ended steel shafts with outer shaft diameter of 324 mm. The piles were double-helix with helix diameter of 610 mm and inter-helix spacing of 1.5 times the helix diameter. The subsurface soil properties at the test site were determined using field and laboratory testing methods. The piles were load tested twice: two weeks and nine months after installation. The load-deflection curves were analyzed and the soil moduli of subgrade reaction were back-calculated to better understand the behavior of the test piles and the effect of pile installation on soil disturbance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".