SERENDIPITY OBSERVATIONS OF FAR INFRARED CIRRUS EMISSION IN THE SPITZER INFRARED NEARBY GALAXIES SURVEY: ANALYSIS OF FAR-INFRARED CORRELATIONS
Bibliographic record
Abstract
We present an analysis of far-infrared (FIR) dust emission from diffuse cirrus clouds. This study is based on serendipitous observations at 160 μm at high-galactic latitude with the Multiband Imaging Photometer onboard the Spitzer Space Telescope by the Spitzer Infrared Nearby Galaxies Survey. These observations are complemented with IRIS data at 100 and 60 μm and constitute one of the most sensitive and unbiased samples of FIR observations at a small scale of diffuse interstellar clouds. Outside regions dominated by the cosmic infrared background fluctuations, we observe a substantial scatter in the 160/100 colors from cirrus emission. We compared the 160/100 color variations to 60/100 colors in the same fields and find a trend of decreasing 60/100 with increasing 160/100. This trend cannot be accounted for by current dust models by changing solely the interstellar radiation field. It requires a significant change of dust properties such as grain size distribution or emissivity or a mixing of clouds in different physical conditions along the line of sight. These variations are important as a potential confusing foreground for extragalactic studies.
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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 | 0.001 |
| 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) | 0.001 | 0.000 |
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".