Bibliographic record
Abstract
Visually transparent solutions of crystallizable polymers in wide concentration and temperature ranges contain supramolecular particles which are fragments of the most perfect crystallites of condensed polymer. Though the fraction of these particles is usually with in 0.001-0.1wt % of the total polymer, their presence in a solution of macromolecules severely affects its physicochemical and technological properties (performance) and complicates (or even does not allow) the application of structurally-sensitive research techniques (e.g. lights cattering, dynamic birefringence, etc.). The parameters of the first-level supramolecular particles (just after visual dissolution) depend on the conditions of dissolution, storage, and the preliminary treatment temperature of the polymer. In wide polymer concentration and temperature ranges, a second level of the supramolecular particles ensemble is formed, with characteristic features of crystallization. From the formation rate of the second-level supramolecular particles, a microliquidus curve for them can be plotted. The paper presents data for the poly (vinyl alcohol) + water system which lack the area of liquid-liquid phase separation. Supramolecular particles parameters (average sizes, numerical and mass-volume concentration) were determined by means of the turbidity spectrum method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".