A submillimetre survey of the kinematics of the Perseus molecular cloud – III. Clump kinematics
Bibliographic record
Abstract
We explore the kinematic properties of dense continuum clumps in the Perseus molecular cloud, derived from our wide-field C18O J = 3 → 2 data across four regions – NGC 1333, IC348/HH211, L1448 and L1455. Two distinct populations are examined, identified using the automated algorithms CLFIND (85 clumps) and GAUSSCLUMPS (122 clumps) on exist-ing SCUBA 850µm data. These kinematic signatures are compared to the clumps ’ dust continuum properties. We calculate each clump’s non-thermal linewidth and virial mass from the associated C18O J = 3 → 2 spectrum. The clumps have supersonic linewidths, 〈σNT/cs 〉 = 1.76 ± 0.09 (CLFIND population) and 1.71 ± 0.05 (with GAUSSCLUMPS). The linewidth distributions suggest the C18O line probes a lower-density ‘envelope ’ rather than a dense inner core. Similar linewidth distributions for protostellar and starless clumps implies protostars do not have a significant impact on their immediate environment. The proximity to an active young stellar cluster seems to affect the linewidths: those in NGC 1333 are greater than elsewhere. In IC348 the proximity to the old IR cluster has little influence, with the linewidths being the smallest of all. The virial analysis suggests that the clumps are bound
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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 | 0.001 | 0.001 |
| 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".