KFPA Examinations of Young STellar Object Natal Environments (KEYSTONE): Hierarchical Ammonia Structures in Galactic Giant Molecular Clouds
Bibliographic record
Abstract
Abstract We present initial results from the K-band Focal Plane Array Examinations of Young STellar Object Natal Environments survey, a large project on the 100 m Green Bank Telescope mapping ammonia emission across 11 giant molecular clouds at distances of 0.9–3.0 kpc (Cygnus X North, Cygnus X South, M16, M17, Mon R1, Mon R2, NGC 2264, NGC 7538, Rosette, W3, and W48). This data release includes the NH3 (1,1) and (2,2) maps for each cloud, which are modeled to produce maps of kinetic temperature, centroid velocity, velocity dispersion, and ammonia column density. Median cloud kinetic temperatures range from 11.4 ± 2.2 K in the coldest cloud (Mon R1) to 23.0 ± 6.5 K in the warmest cloud (M17). Using dendrograms on the NH3 (1,1) integrated intensity maps, we identify 856 dense gas clumps across the 11 clouds. Depending on the cloud observed, 40%–100% of the clumps are aligned spatially with filaments identified in H2 column density maps derived from spectral energy distribution fitting of dust continuum emission. A virial analysis reveals that 523 of the 835 clumps (∼63%) with mass estimates are bound by gravity alone. We find no significant difference between the virial parameter distributions for clumps aligned with the dust-continuum filaments and those unaligned with filaments. In some clouds, however, hubs or ridges of dense gas with unusually high mass and low virial parameters are located within a single filament or at the intersection of multiple filaments. These hubs and ridges tend to host water maser emission, multiple 70 μm detected protostars, and have masses and radii above an empirical threshold for forming massive stars.
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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 | 0.001 |
| 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 | 0.001 |
| 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".