The ALMA Survey of 70 μm Dark High-mass Clumps in Early Stages (ASHES). I. Pilot Survey: Clump Fragmentation
Bibliographic record
Abstract
Abstract The ALMA Survey of 70 μ m dark High-mass clumps in Early Stages (ASHES) is designed to systematically characterize the earliest stages and constrain theories of high-mass star formation. Twelve massive (>500 ), cold (≤15 K), 3.6–70 μ m dark prestellar clump candidates, embedded in infrared dark clouds, were carefully selected in the pilot survey to be observed with the Atacama Large Millimeter/submillimeter Array (ALMA). We have mosaicked each clump (∼1 arcmin 2 ) in continuum and line emission with the 12 m, 7 m, and Total Power (TP) arrays at 224 GHz (1.34 mm), resulting in ∼1.″2 resolution (∼4800 au, at the average source distance). As the first paper in the series, we concentrate on the continuum emission to reveal clump fragmentation. We detect 294 cores, from which 84 (29%) are categorized as protostellar based on outflow activity or “warm core” line emission. The remaining 210 (71%) are considered prestellar core candidates. The number of detected cores is independent of the mass sensitivity range of the observations and, on average, more massive clumps tend to form more cores. We find a large population of low-mass (<1 ) cores and no high-mass (>30 ) prestellar cores (maximum mass 11 ). From the prestellar core mass function, we derive a power-law index of 1.17 ± 0.10, which is slightly shallower than Salpeter. We used the minimum spanning tree (MST) technique to characterize the separation between cores and their spatial distribution, and to derive mass segregation ratios. While there is a range of core masses and separations detected in the sample, the mean separation and mass per clump are well explained by thermal Jeans fragmentation and are inconsistent with turbulent Jeans fragmentation. Core spatial distribution is well described by hierarchical subclustering rather than centrally peaked clustering. There is no conclusive evidence of mass segregation. We test several theoretical conditions and conclude that overall, competitive accretion and global hierarchical collapse scenarios are favored over the turbulent core accretion scenario.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".