High‐Resolution Observations of Interstellar Ca<scp>i</scp>Absorption—Implications for Depletions and Electron Densities in Diffuse Clouds
Bibliographic record
Abstract
We present high-resolution (FWHM ∼ 0.3-1.5 km s -1 ) spectra, obtained with the AAT UHRF, the McDonald Observatory 2.7 m coudé spectrograph, and/or the KPNO coudé feed, of interstellar Ca I absorption toward 30 Galactic stars. Comparisons of the column densities of Ca I, Ca II, K I, and other species—for individual components identified in the line profiles and also when integrated over entire lines of sight—yield information on relative electron densities and depletions (dependent on assumptions regarding the ionization equilibrium). There is no obvious relationship between the ratio N (Ca I)/ N (Ca II) [equal to n e /(Γ/α r ) for photoionization equilibrium] and the fraction of hydrogen in molecular form f (H 2 ) (often taken to be indicative of the local density n H ). For a smaller sample of sight lines for which the thermal pressure ( n H T ) and local density can be estimated via analysis of the C I fine-structure excitation, the average electron density inferred from C, Na, and K (assuming photoionization equilibrium) seems to be independent of n H and n H T . While the electron density ( n e ) obtained from the ratio N (Ca I)/ N (Ca II) is often significantly higher than the values derived from other elements, the patterns of relative n e derived from different elements show both similarities and differences for different lines of sight—suggesting that additional processes besides photoionization and radiative recombination commonly and significantly affect the ionization balance of heavy elements in diffuse interstellar clouds. Such additional processes may also contribute to the (apparently) larger than expected fractional ionizations ( n e / n H ) found for some lines of sight with independent determinations of n H . In general, inclusion of "grain-assisted" recombination does reduce the inferred n e , but it does not reconcile the n e estimated from different elements; it may, however, suggest some dependence of n e on n H . The depletion of calcium may have a much weaker dependence on density than was suggested by earlier comparisons with CH and CN. Two appendices present similar high-resolution spectra of Fe I for a few stars and give a compilation of column density data for Ca I, Ca II, Fe I, and S I.
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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 | 0.000 | 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 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".