YOUNG STELLAR OBJECTS IN THE GOULD BELT
Bibliographic record
Abstract
We present the full catalog of Young Stellar Objects (YSOs) identified in the 18 molecular clouds surveyed by the Spitzer Space Telescope "cores to disks" (c2d) and "Gould Belt" (GB) Legacy surveys. Using standard techniques developed by the c2d project, we identify 3239 candidate YSOs in the 18 clouds, 2966 of which survive visual inspection and form our final catalog of YSOs in the GB. We compile extinction corrected spectral energy distributions for all 2966 YSOs and calculate and tabulate the infrared spectral index, bolometric luminosity, and bolometric temperature for each object. We find that 326 (11%), 210 (7%), 1248 (42%), and 1182 (40%) are classified as Class 0 + I, Flat-spectrum, Class II, and Class III, respectively, and show that the Class III sample suffers from an overall contamination rate by background Asymptotic Giant Branch stars between 25% and 90%. Adopting standard assumptions, we derive durations of 0.40–0.78 Myr for Class 0 + I YSOs and 0.26–0.50 Myr for Flat-spectrum YSOs, where the ranges encompass uncertainties in the adopted assumptions. Including information from (sub)millimeter wavelengths, one-third of the Class 0 + I sample is classified as Class 0, leading to durations of 0.13–0.26 Myr (Class 0) and 0.27–0.52 Myr (Class I). We revisit infrared color–color diagrams used in the literature to classify YSOs and propose minor revisions to classification boundaries in these diagrams. Finally, we show that the bolometric temperature is a poor discriminator between Class II and Class III YSOs.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".