ICEWEAR Program: influences on the ice-induced wear of concrete structures in polar marine environments
Bibliographic record
Abstract
ICEWEAR is a five-year research program, seeking to improve knowledge of surface wear and surface friction influences on the ice-induced wear of concrete structures in polar marine environments. Through the program, a variety of research lines have examined these influences, through ice-concrete interaction laboratory testing, investigations of ice-concrete contact physics, wear reduction strategies and modelling and analysis. The ICEWEAR research program adds to previous research programs over the past five decades that have examined ice-concrete contact phenomena. It also goes further by investigating the hybridization of ASTM and other standardized testing procedures/equipment in order to design new, meaningful, robust ice-concrete tests that can be standardized to better-enable the comparison of results across research programs. This paper will present some of the outputs from the first of these lines of research, with examples of the construction, testing and optimization of new equipment for adhesion, friction, wear and impact ice-concrete contact studies. The paper considers the effects of experimental design, and in particular, the influence of time and pressure on the experimental results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".