Progress on Development of the Electron Spectrometer Telescope
Bibliographic record
Abstract
The Pitch REsolving Spectroscopy for Electron Transport (PRESET) mission aims to measure the pitch-angle dependent electron spectrum in the outer Van Allen Belt’s. This will provide high angular resolution measurements of the electron spectrum within the loss cone for use in development of ionospheric-atmospheric models. To this end the Electron Spectrometer Telescope (EST) is being developed. The EST is a small form factor electron spectrometer based on silicon strip detectors in a telescopic configuration, read out using a set of VATA460.3 ASICs. In this paper we discuss development and testing of the EST hardware. The newly designed BB37(SS) silicon strip detectors are tested for energy and spatial resolution using a VATA460.3 ASIC designed for strip detector read-out. The results are compared with those collected using a commercial pulse processing system connected to the BB37(SS) detectors. The maximum number of strips per channel with acceptable energy resolution is determined to reduce power consumption and instrument cost. A prototype version of the EST containing the custom electronic read out is tested on a high altitude balloon flight. Performance of the current front-end and data acquisition modules and the spectra collected during the flight are discussed.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".