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 A large economic problem in petroleum processing, the plugging of catalytic hydrocracking units, led to a study of the production of large polycyclic aromatic hydrocarbons (PAHs) in this process. Through that work, many other studies of PAHs happened. These included the analysis of coal tar pitches, hydrothermal-vent bitumens, carbon black, Diesel particulate, and fullerene soots. Many new PAHs were synthesized or isolated during the course of these many studies. Keywords: Large polycyclic aromatic hydrocarbonscatalytic hydrocrackingcoal tarhydrothermal ventperhydrocoronenechromatographic retention This paper was presented as an award address as the 20th Internaional Symposiumon Polycyclic Aromatic Compounds, 21–25 August 2005, Toronto, Canada. I would like to acknowledge and thank my many collaborators, most notably Wilt Biggs, Kiyokatsu Jinno, Bill Acree, Max Zander, Philippe Garrigues, Josef Michl, Jasek Waluk, Ken Laali, John Kershaw, Werner Schmidt, Oliver Mullins, Israel Agranat, and Bernie Simoneit. There were many other collaborations and interactions throughout this research and I would also like to thank the many others involved.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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