A colour-excess extinction map of the southern Galactic disc from the VVV and GLIMPSE surveys
Bibliographic record
Abstract
Abstract An improved high-resolution and deep $A_{K_{s}}$ foreground dust extinction map is presented for the Galactic disc area within 295° ≲ l ≲ 350°, −1.0° ≲ b ≲ +1.0°. At some longitudes the map reaches up to |b| ∼ 2.25°, for a total of ∼148 deg2. The map was constructed via the Rayleigh–Jeans colour excess (RJCE) technique based on deep near-infrared (NIR) and mid-infrared (MIR) photometry. The new extinction map features a maximum bin size of 1 arcmin, and relies on NIR observations from the Two Micron All-Sky Survey (2MASS) and new data from ESO’s Vista Variables in the Vía Láctea (VVV) survey, in concert with MIR observations from the Galactic Legacy Infrared Mid-Plane Survey Extraordinaire. The VVV photometry penetrates ∼4 mag fainter than 2MASS, and provides enhanced sampling of the underlying stellar populations in this heavily obscured region. Consequently, the new results supersede existing RJCE maps tied solely to brighter photometry, revealing a systematic underestimation of extinction in prior work that was based on shallower data. The new high-resolution and large-scale extinction map presented here is readily available to the community through a web query interface.
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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 | 0.002 | 0.001 |
| 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) | 0.002 | 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".