Bibliographic record
Abstract
The reclamation of mining operation tailings water is of major concern to the oil sands industry. Naphthenic acids (NAs) are recognized as a major toxic component in tailings water. The acid‐catalyzed esterification of commercially prepared NAs to biodiesel was performed as a test case for the utilization of these toxic compounds. In a series of batch acid‐catalyzed esterification reactions, the influence of reaction temperature, catalyst type, catalyst concentration, and methanol to oil ratio on the esterification was investigated. The NA esterification reactions were found to be positively dependent on temperature and catalyst concentration while large methanol to oil ratios had a negative effect on the esterification. Finally, sulfuric acid was identified as a preferred catalyst for the esterification compared to p‐toluene sulfonic acid. The esterification was completed successfully at the relatively mild conditions used in commercial biodiesel production . © 2012 American Institute of Chemical Engineers Environ Prog, 32: 406‐410, 2013
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 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".