An Interferometric View of H-MM1. I. Direct Observation of NH<sub>3</sub> Depletion
Bibliographic record
Abstract
Abstract Spectral lines of ammonia, NH 3 , are useful probes of the physical conditions in dense molecular cloud cores. In addition to advantages in spectroscopy, ammonia has also been suggested to be resistant to freezing onto grain surfaces, which should make it a superior tool for studying the interior parts of cold, dense cores. Here we present high-resolution NH 3 observations with the Very Large Array and Green Bank Telescope toward a prestellar core. These observations show an outer region with a fractional NH 3 abundance of X (NH 3 ) = (1.975 ± 0.005) × 10 −8 (±10% systematic), but it also reveals that, after all, the X (NH 3 ) starts to decrease above a H 2 column density of ≈2.6 × 10 22 cm −2 . We derive a density model for the core and find that the break point in the fractional abundance occurs at the density n (H 2 ) ∼ 2 × 10 5 cm −3 , and beyond this point the fractional abundance decreases with increasing density, following the power law n −1.1 . This power-law behavior is well reproduced by chemical models where adsorption onto grains dominates the removal of ammonia and related species from the gas at high densities. We suggest that the break-point density changes from core to core depending on the temperature and the grain properties, but that the depletion power law is anyway likely to be close to n −1 owing to the dominance of accretion in the central parts of starless cores.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".