Resolution and sensitivity in computer-automated radioactive particle tracking (CARPT)
Bibliographic record
Abstract
The computer automated radioactive particle tracking (CARPT) is a non-invasive flow monitoring technique used! for measuring mean and fluctuating velocity fields of a traced phase in a multiphase flow system. The method involves accurately monitoring the instantaneous position of a radioactive tracer particle using an array of strategically positioned scintillation detectors. A limitation to the accuracy of CARPT lies in the error associated with the reconstruction of the tracer particle position which affects the space-resolution of the technique. It is of interest, therefore, to minimize this error by choosing wisely the best hardware and an optimal configuration of CARPT detectors’ array. Such choices are currently based on experience, without firm scientific basis. In this paper, through theoretical modeling and simulation, we describe how the accuracy of a radioactive particle tracking setup may be assessed a priori. Through an example of a proposed implementation of CARPT on a gas- solids riser, we demonstrate how this knowledge can be used for choosing the hardware required for the experiment. Finally, we show how the optimal arrangement of detectors can be effected for maximum accuracy for a given amount of monetary investment for the experiment.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".