Direct Waveform Analysis of Ionization Chamber Signals for the SCI-CASTER Project
Bibliographic record
Abstract
A prototype segmented ionization chamber and corresponding waveform analysis algorithm for the segmented conductor ionization chamber for advanced spectroscopy targeting emitters of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> radiation (SCI-CASTER) project at the Simon Fraser University Nuclear Science Laboratory is discussed in this work. Provided that a robust method of extracting data from the detector is implemented, segmented ionization chambers allow for the measurement of both the energy and position of ionizing particles utilizing a single relatively inexpensive detector system. The waveform analyzer written for the SCI-CASTER project operates directly on raw digitized charge drift signals and generates a set of seven piecewise functions that completely describe the input waveform. This reduces the storage and computation time needed to extract timings and amplitudes from the data, allowing for rapid and adaptive offline data analysis. The performance of the waveform analyzer is summarized for a set of experiment runs, and measurements of timing, energy, and a demonstration of the positional sensitivity of the prototype detector are given.
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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 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".