Three-dimensional distribution of hydrogen fluoride gas toward NGC6334 I and I(N)
Bibliographic record
Abstract
Aims. We investigate the spatial distribution of a collection of absorbing gas clouds, some associated with the dense, massive star-forming core NGC6334 I, and others with diffuse foreground clouds. For the former category, we aim to study the dynamical properties of the clouds in order to assess their potential to feed the accreting protostellar cores. Methods. We use spectral imaging from the Herschel SPIRE iFTS to construct a map of HF absorption at 243 micron in a 6x3.5 arcmin region surrounding NGC6334 I and I(N). Results. The combination of new, spatially fully sampled, but spectrally unresolved mapping with a previous, single-pointing, spectrally resolved HF signature yields a 3D picture of absorbing gas clouds in the direction of NGC6334. Toward core I, the HF equivalent width matches that of the spectrally resolved observation. The distribution of HF absorption is consistent with three of the seven components being associated with this dense star-forming envelope. For two of the remaining four components, our data suggest that these clouds are spatially associated with the larger scale filamentary star-forming complex. Our data also implies a lack of gas phase HF in the envelope of core I(N). Using a simple description of adsorption onto and desorption from dust grain surfaces, we show that the overall lower temperature of the envelope of source I(N) is consistent with freeze-out of HF, while it remains in the gas phase in source I. Conclusions. We use the HF molecule as a tracer of column density in diffuse gas (n(H) ~ 10^2 - 10^3 cm^-3), and find that it may uniquely trace a relatively low density portion of the gas reservoir available for star formation that otherwise escapes detection. At higher densities prevailing in protostellar envelopes (>10^4 cm^-3), we find evidence of HF depletion from the gas phase under sufficiently cold conditions.
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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 | 0.000 |
| 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".