Bibliographic record
Abstract
Preliminary testing has shown that Western Research Institute's (WRI) Tank Bottom Recovery and Remediation (TaBoRR{reg_sign}) technology shows promise for heavy oil upgrading. Approximately 70 to 75 wt% of a Canadian Cold Lake bitumen feed was converted to a partially upgraded overhead product that could be transported directly by pipeline or blended with the parent bitumen to produce transportable crude. TaBoRR{reg_sign} was originally developed to remediate tank bottom wastes by producing a distillate product and solid waste. TaBoRR{reg_sign}'s processing steps include breaking a water-oil emulsion, recovering a light hydrocarbon fraction by distillation in a stripper unit, and pyrolyzing the residua reducing it to additional overhead and a benign coke for disposal. Cold Lake bitumen was tested in WRI's bench-scale equipment to evaluate the potential use of TaBoRR{reg_sign} technology for heavy oil upgrading to produce a stable, partially (or fully) upgraded product that will allow diluent-reduced or diluent-free transportation of bitumen or ultra-heavy crudes to market. Runs were conducted at temperatures of low, intermediate and high severity in the stripper to produce stripper overhead and bottoms. The bottoms from each of these runs were processed further in a 6-inch screw pyrolyzer to produce pyrolyzer overhead for blending with the corresponding stripper overheads. Proceeding in this fashion yielded three partially upgraded crudes. The products from TaBoRR{reg_sign} processing, the parent bitumen, and bitumen blends were subjected to stability and compatibility testing at the National Centre for Upgrading Technology (NCUT). Chemical analyses of the overhead product blends have met pipeline specifications for viscosity and density; however the bromine number does not, which might indicate the need for mild hydrotreating. Storage stability tests showed the blends to be stable. The blends were also soluble and compatible with most other Alberta crudes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".