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
I have been blessed throughout my life having wonderful people around me guiding and correcting my path. The acknowledgments section is a very small tribute to all of them. When I started working on the hydrocracker project in the fall of 1998, I really couldn't have imagined that the research work would grow to such great dimensions. IVlany of my fiiends in the industry commented that I am trying to do something very ambitious and some of them cautioned me that I might not get the relevant industrial data. As I am in the final stages of my doctoral research, it becomes very clear to me that this project would not have been possible without the constant support and encouragement from Professor James Riggs. I would like to thank him for the excellent financial support. The expression of my gratitude will not be complete if I forgot to mention the memorable trips to Sunoco Refinery at Samia, Canada (we saw the beautifiil Niagara), Baker Process at Salt Lake City, and numerous visits to meet Professor Froment at Texas A&M
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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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