Exhaustive Baeyer–Villiger oxidation: a tailor-made post-polymerization modification to access challenging poly(vinyl acetate) copolymers
Bibliographic record
Abstract
The discovery of exhaustive (nearly quantitative) post-polymerization modifications (PPM) relies heavily on the efficiency of their corresponding small-molecule protocols. However, the direct translation of existing small-molecule protocols into PPM methods has never been guaranteed due to the intrinsic differences between small-molecule substrates and polymers. Herein, we introduce the direct optimization on polymers (DOP) as a complementary approach to developing exhaustive PPM reactions. As proof of the DOP concept, we present an exhaustive Baeyer-Villiger (BV) post-modification which cannot be accessed by conventional approaches. This user-friendly methodology provides general access to synthetically challenging copolymers of vinyl acetate and more activated monomers (MAMs) including both statistical and narrow-dispersed block copolymers. Furthermore, a scalable one-pot copolymerization/exhaustive BV post-modification procedure was developed to produce such materials showing improved performance over regular PVAc.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".