Low intensity gamma-ray monitor for in-situ solids fraction measurements in liquids
Bibliographic record
Abstract
Abstract A novel detection system has been designed to measure the settling of solids in tailing ponds in order to facilitate the reuse of water in oil sands extraction processing, tailings excavation, transportation and management. The system is based on a weak gamma ray source and an inexpensive scintillator-based detector. The system measures gamma ray photons which are transmitted through the material of interest which are detected by a combined scintillator and Multi Pixel Photon Counter (MPPC) detector. This non-destructive measurement allows the determination of the solids contents profile versus depth in a tailing pond. The attenuation of gamma radiation depends on the density of the solids within the fluid tailings and thus varies with the weight fraction of solids content of the tailings. Modelling of the system was carried out by Geant4 simulations. The system was deployed using a weak 133Ba gamma-ray source together with a simple microprocessor controller readout circuit to analyze the pulse height response of a Cerium doped Lutetium Yttrium Orthosilicate (LYSO (Ce)) scintillator crystal. The detection system is calibrated with the known samples and can measure solids content with a relative precision of within ∼2%.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".