PMSE Centennial: Celebration of Success and New Frontiers in Polymer Materials Science and Engineering
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In 2024, the American Chemical Society (ACS), Division of Polymeric Materials: Science and Engineering (PMSE), celebrated its centennial. This historic occasion was marked at the 2024 Spring ACS Meeting in New Orleans with a Centennial Symposium entitled “ PMSE Centennial: Celebration of Success and New Frontiers in Polymeric Materials Science and Engineering ”. The symposium reflected on past scientific breakthroughs, technological advancements, and new frontiers in the field of polymeric materials science and engineering. Eight thematic areas comprised the symposium: Advanced Manufacturing, AI and Materials Discovery, Biomaterials, Electronic Materials, Energy, Entrepreneurship, Smart Materials, and Sustainability . The 31 distinguished speakers, representing academia, industry, and national laboratories, shared their unique perspectives. Within this Viewpoint, distinguished speakers have expanded on the symposium’s themes, summarizing key takeaways, identifying critical challenges, and exploring opportunities for continued advancements in polymer science.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.084 | 0.027 |
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".