Thermosensitives hydrogels based on poly (ethylene glycol): I. Synthesis, characterization and release
Bibliographic record
Abstract
Des hydrogels thermosensibles bases sur le poly(ethylene glycol) (PEG), diisocyanate (aromatique et /ou aliphatique ) et glycerol ont ete prepares. L'influence du poids moleculaire, de la nature et de la quantite d'agent de reticulation sur les proprietes du gonflement, et le mecanisme de transport de l'eau dans ces hydrogels ont ete etudies. La relation exponentielle M t /M ∞ =kt n est appliquee pour calculer le coefficient (n) qui decrit comportement fickien ou non-fickien du gonflement du reseaux polymeriques. Les coefficients de diffusion d'un agent anti-inflammatoire ont ete calcules et les proprietes du reseau des systemes de l'hydrogel ont ete examinees. Les proprietes des pores microscopiques des hydrogels ont ete determinees par la microscopie electronique a balayage, qui indique une structure poreuse avec des cylindres interconnectes ayant un diametre moyen des pores de 0,4 μm, qui depend de la masse moleculaire du PEG et qui contient quelques imperfections structurales. La liberation de l'agent anti-inflammatoire a ete etudiee par la determination du coefficient de diffusion qui est compris entre 0,4 et 10 10 -6 cm 2 /s.
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 | 0.000 |
| 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) | 0.001 | 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".