A Comparison of Nature-based Solutions and Related Policies for Urban Environment in China and Canada
Bibliographic record
Abstract
The transverse deformation of the tunnel under various loads is unavoidable with the long-term operation of the subway, and the problem of uneven settlement is gradually highlighted. A three-dimensional of tunnel lining model is established in ABAQUS to simulate the uneven settlement and transverse deformation on the safety performance, in which the deformation, internal force, and damage are further analyzed. Based on the simulation, safe settlement values for the shield tunnel with different level of existing transverse deformations (L) are suggested. Because the internal force and damage are not only related to the settlement value (∆) but also to the length of the tunnel where the settlement occurs, the ratio of the settlement value (∆) to the corresponding length (L) of the shield tunnel ∆/L which is called the uneven settlement coefficient is proposed as an index. The uneven settlement coefficient ∆/L is given for different transverse deformations to extend the applicability of the safe settlement values, which provides theoretical support for on-site monitoring and tunnel maintenance to some extent.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".