Computational Simulation of the Random Depolymerization of Linear Polymers Obtained by Step-Polymerization of AB-type Monomers
Bibliographic record
Abstract
This paper presents evaluation results of a computational algorithm developed to simulate the random depolymerization process of a linear polymer having an initial distribution of molecular weights similar to polymers obtained by polycondensation of AB-type monomers, i.e., Flory-Schultz or most probable distribution. Starting from fundamental definitions of this system, as the initial values of the degree of polymerization and chain number (Xno and No, respectively) and the percentage of cleaved bonds (%E), it is confirmed that our algorithm adequately describes the random depolymerization process. Results obtained during the computational simulation indicate that the algorithm properly predicts, among other things, that the inverse of the final polymerization degree (1/Xnf) increases linearly with the applied %E while polydispersity after depolymerization (Df) decreases linearly when the latter parameter increases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".