Skipper-CCD sensors for the Oscura experiment: requirements and preliminary tests
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Oscura is a proposed multi-kg skipper-CCD experiment designed for a dark matter (DM) direct detection search that will reach unprecedented sensitivity to sub-GeV DM-electron interactions with its 10 kg detector array. Oscura is planning to operate at SNOLAB with 2070 m overburden, and aims to reach a background goal of less than one event in each electron bin in the 2–10 electron ionization-signal region for the full 30 kg-year exposure, with a radiation background rate of 0.01 dru.[1 dru (differential rate unit) corresponds to 1 event/kg/day/keV.] In order to achieve this goal, Oscura must address each potential source of background events, including instrumental backgrounds. In this work, we discuss the main instrumental background sources and the strategy to control them, establishing a set of constraints on the sensors' performance parameters. We present results from the tests of the first fabricated Oscura prototype sensors, evaluate their performance in the context of the established constraints and estimate the Oscura instrumental background based on these results.
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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) | 0.000 | 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 it