SHARC: Silicon Highly-segmented Array for Reactions and Coulex used in conjunction with the TIGRESS γ-ray spectrometer
Bibliographic record
Abstract
The combination of γ-ray spectroscopy and charged-particle spectroscopy is a powerful tool for the study of nuclear reactions with beams of nuclei far from stability. This paper presents a new silicon detector array, SHARC, the Silicon Highly-segmented Array for Reactions and Coulex. The array is used at the radioactive-ion-beam facility at TRIUMF (Canada), in conjunction with the TIGRESS γ-ray spectrometer, and is built from custom Si-strip detectors utilising a fully digital readout. SHARC has more than 50% efficiency, approximately 1000-strip segmentation, angular resolutions of Δθ ≈ 1.3 deg and Δφ ≈ 3.5 deg, 25-30 keV energy resolution, and thresholds of 200 keV for up to 25 MeV particles. SHARC is now complete, and the experimental program in nuclear astrophysics and nuclear structure has commenced. © 2011 IOP Publishing Ltd and SISSA.
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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 | 0.000 |
| 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 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".