Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT: This perspective provides the collective opinions of a dozen chemical reaction engineers from academia and industry. In this sequel to the “Vision 2020: Reaction Engineering Roadmap,” published in 2001, we provide our opinions about the field of reaction engineering by addressing the current situation, identifying barriers to progress, and recommending research directions in the context of four industry sectors (basic chemicals, specialty chemicals, pharmaceuticals, and polymers) and five technology areas (reactor system selection, design and scale-up, chemical mechanism development and property estimation, catalysis, nonstandard reactor types, and electrochemical systems). Our collective input in this report includes numerous recommendations regarding research needs in the field of reaction engineering in the coming decades, including guidance for prioritizing efforts in workforce development, measurement science, and computational methods. We see important roles for reaction engineers in the plastics circularity challenge, decarbonization of processes, electrification of chemical reactors, conversion of batch processes to continuous processes, and development of intensified, dynamic reaction processes.
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.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it