Characterization of Iron-Bearing Particles in Athabasca Oil Sands
Bibliographic record
Abstract
Iron-bearing particles in two Athabasca oil sands ore samples have been characterized in this study by electron microscopy. One sample was taken from a “good processing ore” and one from a “poor processing ore”. These samples were subjected to a batch extraction process and the resulting solids in the primary froth were characterized. While iron-bearing minerals such as magnetite and hematite were common in both ore samples, pyrite and goethite were only found in the poor processing ore and wustite was identified only in the good processing ore. The iron-bearing particles were concentrated in the primary froth stream from batch extraction, and their sizes varied from a few nanometers to several hundred nanometers. The nanometer scale iron bearing minerals have been identified in two different arrangements. Nanoscale iron-bearing minerals either form patches on top of relatively large (200–300 nm) clay particles, or they combine with nanoscale clay and toluene insoluble organic material to form mineral-organic aggregates.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".