Bitumen Extraction from Oil Sands Ore-Water Slurry Using CaO (Lime) and/or Ozone
Bibliographic record
Abstract
Abstract Bitumen extraction efficiency is increased in oil sands ore-water slurry based extraction process by increasing solubility of naturally occurred asphaltic acids by addition of CaO (lime) and/or by oxidation of bitumen asphaltenes by Ozone (O3) to surfactant species, at as low as 35 °C temperature. Experimental findings suggest that a non-caustic bitumen extraction process (i.e. without using NaOH as extraction process aid) could be used commercially by conditioning the oil sands ore-water slurry with CaO and/or Ozone, which would allow high extraction efficiencies at about 35 °C temperature, reduce energy consumption and CO2 emission for the extraction of bitumen and eliminate the accumulation of Na+ ions in the recycled release water. Further tests are on-going to provide sufficient data for the commercial implementation of the use of CaO and/or Ozone at oil sands-ore water slurry based extraction plants.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".