CHARACTERIZING THE STRUCTURE OF DIFFUSE EMISSION IN Hi-GAL MAPS
Bibliographic record
Abstract
We present a study of the structure of the Galactic interstellar medium (ISM) through the Δ-variance technique, related to the power spectrum and the fractal properties of infrared/submillimeter maps. Through this method, it is possible to provide quantitative parameters, which are useful for characterizing different morphological and physical conditions, and better constraining the theoretical models. In this respect, the Herschel Infrared Galactic Plane Survey, carried out at five photometric bands from 70 to 500 μm, constitutes a unique database for applying statistical tools to a variety of regions across the Milky Way. In this paper, we derive a robust estimate of the power-law portion of the power spectrum of four contiguous 2° × 2° Hi-GAL tiles located in the third Galactic quadrant (217° ≲ ℓ ≲ 225°, −2° ≲ b ≲ 0°). The low level of confusion along the line of sight, testified by CO observations, makes this region an ideal case. We find very different values for the power spectrum slope from tile to tile but also from wavelength to wavelength (2 ≲ β ≲ 3), with similarities between fields attributable to components located at the same distance. Thanks to comparisons with models of turbulence, an explanation of the determined slopes in terms of the fractal geometry is also provided, and possible relations with the underlying physics are investigated. In particular, an anti-correlation between ISM fractal dimension and star formation efficiency is found for the two main distance components observed in these fields. A possible link between the fractal properties of the diffuse emission and the resulting clump mass function is discussed.
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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 | 0.001 | 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) | 0.000 | 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".