Quasi-homogenous approximation for description of the properties of dispersed systems. the basic approaches to model hardening processes in nanodispersed silica systems. Part II. hardening processes from the point of view of statistical physics
Bibliographic record
Abstract
The paper deals with possibilities to use quasi-homogenous approximation for discription of properties of dispersed systems.The authors applied statistical polymer method based on consideration of average structures of all possible macromolecules of the same weight.The equiations which allow evaluating many additive parameters of macromolecules and the systems with them were deduced.Statistical polymer method makes it possible to model branched, cross-linked macromolecules and the systems with them which are in equilibrium or non-equilibrium state.Fractal analysis of statistical polymer allows modeling different types of random fractal and other objects examined with the mehods of fractal theory.The method of fractal polymer can be also applied not only to polymers but also to composites, gels, associates in polar liquids and other packaged systems.There is also a description of the states of colloid solutions of silica oxide from the point of view of statistical physics.This approach is based on the idea that colloid solution of silica dioxide -sol of silica dioxide -consists of enormous number of interacting particles which are always in move.The paper is devoted to the research of ideal system of colliding but not interacting particles of sol.The analysis of behavior of silica sol was performed according to distribution Maxwell-Boltzmann and free path length was calculated.Using this data the number of the particles which can overcome the potential barrier in collision was calculated.To model kinetics of sol-gel transition different approaches were studied.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".