Intrinsic, Observed, and Retrieved Properties of Interstellar Turbulence
Bibliographic record
Abstract
We generate synthetic observations of three-dimensional, self-gravitating MHD simulations of the interstellar medium (ISM) to evaluate the ability of principal component analysis (PCA) to measure the scale dependence of turbulent velocity fluctuations in molecular clouds. Scaling exponents, α, observationally obtained from the coupled characteristic scales for line profile variability in velocity, δ v , and in space, L , where δ v ∝ L α , are compared with the intrinsic scaling exponents of the MHD velocity fields. We determine the approximate structure function order at which PCA operates in order to then verify a previously established calibration of the PCA method. We also analyze the statistical properties of projected velocity line centroid fields, including effects of intermittent velocity fluctuations, density inhomogeneity, and opacity, and examine the relationship of the projected two-dimensional statistics to the intrinsic three-dimensional statistics. Using PCA, we infer steep three-dimensional energy spectra in the molecular ISM, generally steeper than can be accounted for by Kolmogorov turbulence or possibly even shock-dominated turbulence.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.066 | 0.022 |
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".