Heavy Molecular and Metallic Ions in the Magnetosphere
Bibliographic record
Abstract
Abstract Observations and present knowledge of heavy ions with mass ≥ 27 in the magnetosphere are reviewed. There are four ultimate sources of these heavy ions: the solar wind (mainly high charge-state atomic ions), the ionosphere (mainly molecular ions), the atmospheric metal layers that originate ultimately from ablation of meteoroids and possibly space debris (low charge-state metallic ions and metal-rich molecular ions), and lunar surface and exosphere (low charge-state metallic and molecular ions). The upstream heavy ions (solar wind origin and lunar origin) give independent information on the ion entry routes to the magnetosphere from proton (H+) and alpha particles (He++): with similar mass-per-charge (m/q) values, or gyroradius, for the solar wind origin, and much larger gyroradius for the lunar origin. The lunar origin ions also give independent insights from laboratory observations on the sputtering processes. The atmospheric origin molecular and metallic ions are essential in understanding energization, ionization altitudes, and upward transport in the ionosphere during various ionospheric and magnetospheric conditions. These ions are also important when considering the evolution of the Earth’s atmosphere on the geological timescale. Only a few terrestrial missions have been equipped with instrumentation dedicated to separate these molecular and metallic ions, within only a limited energy range (cold ions of < 50 eV and energetic ions of ∼ 100 keV or more) and a limited mass range (mainly ≤ 40 amu). This is far too limited to make any quantitative discussion on the very heavy ions in the magnetosphere. For example, the existing data are far from sufficient for determining the dominant contributor from the four possible sources, or even to rule out any of the possible sources as a substantial contributor. Under this circumstance, it is worth to re-examine, using available tools, the existing data from the past and on-going missions, including those not designed for the required mass separation, to search for these ions. The purpose of this review is to summarize the availability of these datasets and tools. This review also shows some examples of combinations of different datasets that provide important indications of the sources of these heavy ions and their amounts that have been overlooked to date. Finally, we note the possible future contamination of specific masses (mainly aluminum (Al), but also lithium (Li), iron (Fe), nickel (Ni), copper (Cu), titanium (Ti) and germanium (Ge)) by the ablation of re-entering human-made objects in space (debris and alive satellites) in the coming decades. This possibility argues the need for dedicated observations of magnetospheric and ionospheric metallic ions before these metallic ions of space debris origin start to dominate over the natural contribution. The required observations can be performed with the available designs of space instrumentation and available ground-based instruments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".