FAR-INFRARED OBSERVATIONS OF THE VERY LOW LUMINOSITY EMBEDDED SOURCE L1521F-IRS IN THE TAURUS STAR-FORMING REGION
Bibliographic record
Abstract
We investigate the environment of the very low luminosity object L1521F-IRS using data from the Taurus Spitzer Legacy Survey. The MIPS 160 μm image shows both extended emission from the Taurus cloud and emission from multiple cold cores over a 1° × 2° region. Analysis shows that the cloud dust temperature is 14.2 ± 0.4 K and the extinction ratio is A 160 / A K = 0.010 ± 0.001 up to A V ∼ 4 mag. We find κ 160 = 0.23 ± 0.046 cm 2 g −1 for the specific opacity of the gas–dust mixture. Therefore, for dust in the Taurus cloud we find that the 160 μm opacity is significantly higher than that measured for the diffuse interstellar medium, but not too different from dense cores, even at modest extinction values. Furthermore, the 160 μm image shows features that do not appear in the IRAS 100 μm image. We identify six regions as cold cores, i.e., colder than 14.2 K, all of which have counterparts in extinction maps or C 18 O maps. Three of the six cores contain embedded young stellar objects, which demonstrates the cores are sites of current star formation. We compare the effects of L1521F-IRS on its natal core and find there is no evidence for dust heating at 160 or 100 μm by the embedded source. From the infrared luminosity L TIR = 0.024 L ☉ we find , thus confirming the source's low luminosity. Comparison of L1521F-IRS with theoretical simulations for the very early phases of star formation appears to rule out the first core collapse phase. The evolutionary state appears similar to or younger than the class 0 phase, and the estimated mass is likely to be substellar.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".