Mid-infrared Extinction toward the Galactic Center
Bibliographic record
Abstract
Abstract We determine the mid-infrared (MIR, ∼5–22 μ m) extinction toward the Galactic center using MIRI/Medium-Resolution Spectrometer (MRS) integral field unit observations of the central 3″ × 3″ region (near 5 μ m) to 7″ × 7″ region (near 22 μ m). To measure the MIR extinction, we employ two approaches: modeling the intrinsic-to-observed dust thermal spectrum and assessing the differential extinction between hydrogen recombination lines. Expanding on prior work, we directly model the dust-opacity distribution along the line of sight, and we make available a Python code that provides a flexible tool for deriving intrinsic dust emission spectra. We confirm the spatial variability of extinction across the field, demonstrating that dusty sources—such as IRS 29N—exhibit higher local extinction. Furthermore, we verify the absence of emission features from polycyclic aromatic hydrocarbons in the MIR spectra of the Galactic center. Using the two complementary methods, we derive a refined “best guess” MIR extinction law for Sgr A* and the surrounding Galactic-center region. By applying the extinction law to an MIR flare measurement discussed in a companion paper, we estimate a residual relative extinction uncertainty for the short MIRI/MRS grating of the order of 0.2 mag from ∼5 to ∼18 μ m and ∼0.3 mag from ∼18 to ∼22 μ m, consistent with our uncertainty estimate.
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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 | 0.001 |
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".