Temperature Effect on Dynamic Behaviors of Cis-Polyisoprene Chain
Bibliographic record
Abstract
A novel structure-preserving method, named as stochastic generalized multi-symplectic method, is proposed to analyze the temperature effect on the dynamic characteristics hided in the motion of the cis-polyisoprene chain in this paper. Ignoring the dynamic backflow and the exhaust volume effect, the motion of the Gaussian chain in linear polymers can be described as the Langevin model, which can be written into the stochastic generalized multi-symplectic form. For this stochastic generalized multi-symplectic form, a box structure-preserving scheme is constructed to simulate the motion of the cis-polyisoprene chain. From the simulation results, the temperature effects on the dynamic behaviors around the glass transition temperature and the viscous flow temperature of cis-polyisoprene are investigated. The structure-preserving method for analyzing the temperature effect on the dynamic characteristics of the cis-polyisoprene chain presented in this paper proposes a new way to study some dynamic characteristics of complex fluid systems.
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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".