Detecting Structural Polydispersity in Branched Polybutadienes
Bibliographic record
Abstract
The structural details of a set of highly entangled H-shaped polybutadienes (PBDs) prepared by anionic polymerization were examined in detail by three reputable laboratories using size exclusion chromatography (SEC) and temperature gradient interaction chromatography (TGIC). While SEC data indicated that samples having the desired structures (i.e., nearly monodisperse H-shaped polymer) had been produced, additional SEC data from other laboratories showed that the samples were structurally more complex than originally thought. TGIC data revealed that while the samples did not contain high molecular weight byproducts, they did contain low molecular weight byproducts. To discern these structural details of the branched PBDs, small amounts of sample were fractionated by TGIC. By combining knowledge of the polymerization process with the TGIC data of fractionated samples, it was possible to work out the detailed compositions of the samples and the branching structures of each component.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".