Charting nearby stellar systems: The intensity of Galactic cosmic rays for a sample of solar-type stars
Bibliographic record
Abstract
Galactic cosmic rays are important for exoplanetary atmospheres. They can contribute to the formation of hazes, prebiotic molecules and atmospheric electrical circuits. A number of so-called fingerprint ions, such as oxonium, have been identified from chemical modelling which are thought to be signatures of ionisation by energetic particles, such as Galactic cosmic rays. These fingerprint ions may be observed in exoplanetary atmospheres with upcoming JWST observations.I will discuss our recent results that model the propagation of Galactic cosmic rays through the stellar winds of a number of nearby solar-type stars. Our sample comprises of 5 well-observed solar-type stars that we have constructed well-constrained stellar wind models for. This allows us to calculate the transport of Galactic cosmic rays through these systems. I will present our results of the Galactic cosmic ray fluxes that reach (a) the habitable zone and (b) the location of known exoplanets. The systems show a variety of behaviour and I will discuss the most promising systems for upcoming JWST observations.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".