Interstellar Turbulence. II. Energy Spectra of Molecular Regions in the Outer Galaxy
Bibliographic record
Abstract
The multivariate tool of principal component analysis (PCA) is applied to 23 fields in the FCRAO CO Survey of the Outer Galaxy. PCA enables the identification of line profile differences, which are assumed to be generated from fluctuations within a turbulent velocity field. The variation of these velocity differences with spatial scale within a molecular region is described by a singular power law, δ v = cL α , which can be used as a powerful diagnostic to turbulent motions. For the ensemble of 23 fields, we find a mean value = 0.62 ± 0.11. From a recent calibration of this method using fractal Brownian motion simulations (Brunt & Heyer), the measured velocity difference-size relationship corresponds to an energy spectrum, E ( k ), which varies as k -β , where β = 2.17 ± 0.31. We compare our results to both decaying and forced hydrodynamic simulations of turbulence. We conclude that energy must be continually injected into the regions to replenish that lost by dissipative processes such as shocks. The absence of large, widely distributed shocks within the targeted fields suggests that the energy is injected at spatial scales less than several parsecs.
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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 | 0.000 | 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".