Structural Dynamic Study of Roof Waterproofing Materials
Bibliographic record
Abstract
The present research was aimed to develop the scientific applied principles and technologies of composite bituminous materials for civil engineering based on the investigation of the structures of polymer modifier and bitumen-polymer binder (BPB) on its basis with the use of nuclear magnetic resonance (NMR). The method of pulsed NMR was chosen as one of the rapid analysis methods that can be used for the analysis of bitumen-polymer systems, especially when assessing the group chemical composition of residual oil feedstock (ROF), bitumens and composite materials based on them. Using the method of pulsed NMR the regularities of the impact of modifier component composition on the changes of structural-group composition of the original and modified products were specified. Based on the results of research the optimal ratio of bitumen-polymer binder components was investigated, the manufacturability of the process for obtaining of composite bituminous materials for civil engineering with the aim of optimizing the quality of the final products was evaluated. Pulsed NMR - spectroscopy is suggested as input and output quality control of bituminous products. The regularities of redistribution of the phases with different molecular mobility and their relationship with the binder components were investigated. Rapid technique for quantifying the content of polymer in the solvent was developed.
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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 | 0.000 |
| 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) | 0.003 | 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".