Probing the evolution of molecular cloud structure
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Bibliographic record
Abstract
<i>Context. <i/>Probability distribution of densities is a fundamental measure of molecular cloud structure, containing information on how the material arranges itself in molecular clouds.<i>Aims. <i/>We derive the probability density functions (PDFs) of column density for a complete sample of prominent molecular cloud complexes closer than pc. For comparison, additional complexes at pc are included in the study.<i>Methods. <i/>We derive near-infrared dust extinction maps for 23 molecular cloud complexes, using the nicest colour excess mapping technique and data from the 2MASS archive. The extinction maps are then used to examine the column density PDFs in the clouds.<i>Results. <i/>The column density PDFs of most molecular clouds are well-fitted by log-normal functions at low column densities (0.5 mag mag, or ). But at higher column densities prominent power-law-like wings are common. In particular, we identify a trend among the PDFs: active star-forming clouds always have prominent non-log-normal wings. In contrast, clouds without active star formation resemble log-normals over the whole observed column density range or show only low excess of higher column densities. This trend is also reflected in the cumulative forms of the PDFs, showing that the fraction of high column density material is significantly larger in star-forming clouds. These observations agree with an evolutionary trend where turbulent motions are the main cloud-shaping mechanism for quiescent clouds, but the density enhancements induced by them quickly become dominated by gravity (and other mechanisms), which is in turn strongly reflected by the shape of the column density PDFs. The dominant role of the turbulence is restricted to the very early stages of molecular cloud evolution, comparable to the onset of active star formation in the clouds.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it