G11.92–0.61-MM2: A BONAFIDE MASSIVE PRESTELLAR CORE?
Bibliographic record
Abstract
Core accretion models of massive star formation require the existence of stable massive starless cores, but robust observational examples of such objects have proven elusive. We report subarcsecond-resolution Submillimeter Array (SMA) 1.3 mm, 1.1 mm, and 0.88 mm and Very Large Array 1.3 cm observations of an excellent massive starless core candidate, G11.92−0.61–MM2, initially identified in the course of studies of GLIMPSE Extended Green Objects (EGOs). Separated by ∼7 2 from the nearby MM1 protostellar hot core, MM2 is a strong, compact dust continuum source (submillimeter spectral index α = 2.6 ± 0.1), but is devoid of star formation indicators. In contrast to MM1, MM2 has no masers, no centimeter continuum, and no (sub)millimeter wavelength line emission in ∼24 GHz of bandwidth observed with the SMA, including N 2 H + (3–2), HCO + (3–2), and HCN(3–2). Additionally, there is no evidence for an outflow driven by MM2. The (sub)millimeter spectral energy distribution of MM2 is best fit with a dust temperature of ∼17–19 K and luminosity of ∼5–7 L ☉ . The combined physical properties of MM2, as inferred from its dust continuum emission, are extreme: M ≳ 30 M ☉ within a radius <1000 AU, N >10 25 cm −2 and >10 9 cm −3 . Comparison of the molecular abundance limits derived from our SMA observations with gas-grain chemical models indicates that extremely dense ( n (H) ≫ 10 8 cm −3 ), cold (<20 K) conditions are required to explain the lack of observed (sub)millimeter line emission, consistent with the dust continuum results. Our data suggest that G11.92−0.61–MM2 is the best candidate for a bonafide massive prestellar core found to date, and a promising target for future higher-sensitivity observations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".