UWISH2 - the UKIRT Widefield Infrared Survey for H2
Bibliographic record
Abstract
We present the goals and preliminary results of an unbiased, near-infrared, narrow-band imaging survey of the first galactic quadrant (10° < l < 65°; −13 < b < +13). This area includes most of the giant molecular clouds and massive star forming regions in the Northern hemisphere. The survey is centred on the 1–0 S(1) rovibrational line of H2, a proven tracer of hot, dense molecular gas in star-forming regions, around evolved stars, and in supernova remnants. The observations complement existing and upcoming photometric surveys (Spitzer-GLIMPSE, UKIDSS-GPS, JCMT-JPS, AKARI, Herschel Hi-GAL, etc.), though we probe a dynamically active component of star formation not covered by these broad-band surveys. Our narrow-band survey is currently more than 60 per cent complete. The median seeing in our images is 0.73 arcsec. The images have a 5σ detection limit of point sources of K∼ 18 mag and the surface brightness limit is 10−19 W m−2 arcsec−2 when averaged over our typical seeing. Jets and outflows from both low- and high-mass young stellar objects are revealed, as are new planetary nebulae and – via a comparison with earlier K-band observations acquired as a part of the UKIDSS GPS – numerous variable stars. With their superior spatial resolution, the UWISH2 data also have the potential to reveal the true nature of many of the extended green objects found in the GLIMPSE survey.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".