Bibliographic record
Abstract
The Earth's magnetosphere is composed of energetic electrons and protons. It is important to verify average populations and energy distributions of these particles and quantify the effects of geomagnetic events on their populations and energy distributions. Abrupt changes have been observed in the energy and distribution of protons during magnetic storms creating a large population of very energetic (> 1 MeV) protons in the slot region of the Earth's Van Allen belts. A few attempts have been made in the past to investigate the sources and loss mechanism of these energetic particles. We have carried out detailed modelling of a High Energy Proton Telescope (HEPT) proposed as a scientific instrument for the proposed Canadian Outer Radiation Belt Injection, Transport, and Loss Satellite (ORBITALS) mission. HEPT is capable of measuring the energetic proton and electron distributions in the energy range of 3-120 MeV for protons and 3-20 MeV for electrons. The detector consists of two heads, one to cover the range of 3 to 26 MeV protons and the second to cover the range of 26 to 120 MeV protons with total view angles of $18^{o}$ and $36^{o}$, respectively. The detector efficiency and geometric factors were calculated numerically using the GEANT4 high energy physics modelling code. In addition, model calculations were carried out to compare the model instrument performance with experimental measurements carried out at the TRIUMF accelerator facility giving good agreement. The results obtained indicate that the detector design would be suitable for a satellite mission to study energetic particle distributions during energetic solar particle events.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".