Extended Abstract: Estimation of froth quality using Bayesian information synthesis
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the design of soft sensors for estimation of froth quality in oil sands extraction processes. One of the most important quality indexes for bitumen froth is the water content. Due to the variations of oil sands compositions and the complexity of the extraction process, existing hardware sensors are not reliable enough to provide accurate water content information. Laboratory analysis result is obtained off-line with large sampling interval and irregular time delay. Therefore, it is not sufficient for real-time monitoring and control. Bayesian information synthesis is proposed to fuse all the existing information to produce more reliable and more accurate real-time froth quality information. The technique has been applied in oil sands extraction units in Syncrude Canada Limited. Application results illustrate its promising perspectives for soft sensor development.
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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 | 0.001 |
| 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 | 0.001 |
| 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