The Spectral Energy Distribution of Self‐gravitating Interstellar Clouds. I. Spheres
Bibliographic record
Abstract
We derive the spectral energy distribution (SED) of dusty, isothermal, self-gravitating, stable and spherical clouds externally heated by the ambient interstellar radiation field (ISRF). For a given radiation field and dust properties, the radiative transfer problem is determined by the pressure of the surrounding medium and by the cloud mass expressed as a fraction of the maximum stable cloud mass above which the clouds become gravitationally unstable. To solve the radiative transfer problem, a ray-tracing code is used to accurately derive the light distribution inside the cloud. This code considers both anisotropic scattering on dust grains and multiple scattering events. The dust properties inside the clouds are assumed to be the same as in the diffuse interstellar medium in our Galaxy. We analyze the effect of the pressure, the critical mass fraction, and the ISRF on the SED and present brightness profiles in the visible, the IR/FIR, and the submillimeter/millimeter regime with the focus on the scattered emission and the thermal emission from PAH molecules and dust grains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".