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
Strategies for heavy oil desulfurization were evaluated by reviewing desulfurization literature and critically assessing the viability of the various methods for heavy oil. The desulfurization methods including variations thereon that are discussed include hydrodesulfurization, extractive desulfurization, oxidative desulfurization, biodesulfurization and desulfurization through alkylation, chlorinolysis, and by using supercritical water. Few of these methods are viable and/or efficient for the desulfurization of heavy oil. This is mainly due to the properties of the heavy oil, such as high sulfur content, high viscosity, high boiling point, and refractory nature of the sulfur compounds. The approach with the best chance of leading to a breakthrough in desulfurization of heavy oil is autoxidation followed by thermal decomposition of the oxidized heavy oil. There is also scope for synergistically employing autoxidation in combination with biodesulfurization and hydrodesulfurization.
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 | 0.001 |
| 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