The Rich Mid-Infrared Environments of Two Highly Obscured X-Ray Binaries: <i>Spitzer</i> Observations of IGR J16318-4848 and GX 301-2
Bibliographic record
Abstract
We present the results of Spitzer spectroscopic observations of two highly obscured massive X-ray binaries: IGR J16318-4848 and GX 301-2. Our observations reveal for the first time the extremely rich mid-infrared environments of this type of source, including multiple continuum emission components (a hot component with T > 700 K and a warm component with T ~ 180 K) with apparent silicate absorption features, numerous H I recombination lines, many forbidden lines of low ionization potential, and pure rotational H 2 lines. This indicates that both sources have hot and warm circumstellar dust, ionized stellar winds, extended low-density ionized regions, and photodissociated regions. It appears difficult to attribute the total optical extinction of both sources to the hot and warm dust, which suggests that there could be an otherwise observable colder dust component responsible for most of the optical extinction and silicate absorption features. The observed mid-infrared spectra are similar to those from luminous blue variables, indicating that the highly obscured massive X-ray binaries may represent a previously unknown evolutionary phase of X-ray binaries with early-type optical companions. Our results highlight the importance and utility of mid-infrared spectroscopy for investigating highly obscured X-ray binaries.
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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 | 0.001 |
| 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".