Limitations of Gold’s formula for predicting ice thickness requirements for heavy equipment
Bibliographic record
Abstract
Common practice for determining the required ice thickness for vehicles and equipment relies on Gold’s formula as outlined in provincial and territorial publications relating to ice safety. This practice persists despite recent advances in ice engineering knowledge that provide more comprehensive design methods utilizing allowable stress design approaches. The authors have identified that the use of Gold’s formula for determining required ice thickness may lead to unsafe practices when utilized in the context of heavy construction equipment, increasing the risk of ice breakthrough to personnel and equipment. The authors use recent design examples to demonstrate instances in which the use of Gold’s formula results in predicted flexural tensile stresses in the ice cover that exceed the maximum design stress recommended in contemporary literature. In the case of large excavators (53 metric tonnes) and heavy dozers (40 metric tonnes), as examples, the use of Gold’s formula for determining the required ice thickness will result in predicted flexural tensile stresses that exceed the recommended maximum design stress by 56%–71%.
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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 | 0.001 | 0.001 |
| 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".