Bibliographic record
Abstract
Characterization study of the CsI(Tl) detector array, by Corwin Trottier, submitted on April 28, 2013:The ISAC Charged Particle Spectroscopy Station (IRIS) at TRIUMF, Vancouver, Canada uses CsI(Tl)-a 16 component detector array composed of thallium-doped cesium iodide-for high resolution study of nuclear reactions.Each CsI(Tl) detector was characterized by studying its response and determining its Q-value resolution for scattering reactions.The elastic scattering of p( 18 O, p) 18 O among similar higherenergy inelastic reactions were examined during the calibration process.Data from several experimental runs were compared to kinematics curves to calibrate the energy response of each CsI(Tl) sector.Elastic and inelastic Q-value peaks were corrected for dependence on scattering angle and measured for resolution.CsI(Tl) is an inorganic scintillator crystal, which is coupled to a photodiode.The annular-type detector array consists of 16 identically designed sectors.Each sector was characterized separately in order to describe the detector array as a whole.In general, the characterized CsI(Tl) detector will detect hydrogen isotope reaction products that were scattered from a target of similar atomic structure.Motivation for this study includes the future use of the CsI(Tl) detector in nuclear reactions involving radioactive ion beams at IRIS.These reactions can provide further understanding of the nuclear force, shell structure and general theory of unstable exotic nuclei.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".