Determination of reactivity ratios for the copolymerization of poly(acrylic acid‐<i>co</i>‐itaconic acid)
Bibliographic record
Abstract
ABSTRACT Monomer reactivity ratios are important parameters used in copolymerization kinetics to predict the rate of polymerization, copolymer composition and monomer sequence length, and by extension, molecular weight and distribution of the final product. Batch aqueous solution copolymerizations of acrylic acid (AA) and itaconic acid (IA) are performed at various feed compositions. Polymerizations are categorized into low (<11 wt %) conversion and higher (< 30 wt %) conversion data sets for analysis. Due to the limited solubility of IA in the reaction mixture, the feed composition of IA in all polymerizations is constrained to lower than 25 mol %. Conversion is determined by gravimetric methods, and copolymer composition via 1 H‐NMR spectroscopy. All data are analyzed using the error‐in‐variables model (EVM) method. Two analyses are used, one with the EVM approach and another with a novel Direct Numerical Integration (DNI) coupled with the EVM method. The DNI/EVM approach yields values of r AA = 0.36 and r IA = 1.62 for the reactivity ratios. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 44014.
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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 | 0.000 |
| 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 | 0.001 |
| 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".