Modeling the reversible addition–fragmentation transfer polymerization process
Bibliographic record
Abstract
Abstract A kinetic model has been developed for reversible addition–fragmentation transfer (RAFT) polymerization with the method of moments. The model predicts the monomer conversion, number‐average molecular weight, and polydispersity of the molecular weight distribution. It also provides detailed information about the development of various types of chain species during polymerization, including propagating radical chains, adduct radical chains, dormant chains, and three types of dead chains. The effects of the RAFT agent concentration and the rate constants of the initiator decomposition, radical addition, fragmentation, disproportionation, and recombination termination of propagating radicals and cross‐termination between propagating and adduct radicals on the kinetics and polymer chain properties are examined with the model. © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 1553–1566, 2003
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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 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".