Mid-IR spectro-imaging observations with the ISOCAM CVF: Final reduction and archive
Bibliographic record
Abstract
Mid-IR (5–m) Spectro-Imaging observations towards several hundred sky positions were obtained with the Infrared Space Observatory Camera (ISOCAM), and a Circular Variable Filter (CVF) that provided spectral resolution R = ~ 45 over a 3′ field (for 6, and 12´´ pixels, proportionally smaller for the observations carried with the 3, and 1.5´´ pixels). The wavelength range includes dust bands – in particular several of the aromatic carbon bands – fine structure lines from ionized gas, and H2 rotational lines. The observed fields comprise nearby and distant galaxies, Galactic and Extragalactic star forming regions, the Galactic diffuse emission, nearby molecular clouds, infrared cirrus, young stellar objects, evolved stars, and Solar System targets. We present the final data reduction procedure that improves on the standard pipeline reduction in several ways, mainly the subtraction of zodiacal light, that of stray light associated with the uniform, most often dominant, emission component and the correction of a pixel dependent wavelength shift. We also propose a correction of the largest astrometry errors introduced by the optics. We have processed most of the ISOCAM CVF observations and made the results available on the ISO archive for public use. The processed data may be routinely used over the full sensitivity range of the instrument down to a brightness as faint as a few % of the zodiacal emission. For extended emission, the CVF observations represent a data base with a lasting value which can serve many scientific goals and motivate follow-up observations in particular with the Spitzer Space Telescope spectrometer.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.025 |
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".