The Exoplanet Climate Infrared TElescope (EXCITE)
Bibliographic record
Abstract
Although there are a large number of known exoplanets, there is little data on their global atmospheric properties. Phase-resolved spectroscopy of transiting planets – continuous spectroscopic observation of planets during their full orbits – probes varied depths and longitudes in the atmospheres thus measuring their three-dimensional thermal and chemical structure and contributing to our understanding of their global circulation. Planets with characteristics suitable for atmospheric characterization have orbits of several days, so phase curve observations are highly resource intensive, especially for shared use facilities. The Exoplanet Climate Infrared TElescope (EXCITE) is a balloon-borne near-infrared spectrometer designed to observe from 1 to 5 μm to perform phaseresolved spectroscopy of hot Jupiters. Flying from a long duration balloon (LDB) platform, EXCITE will have the stability to continuously stare at targets for days at a time and the sensitivity to produce data of the quality and quantity needed to significantly advance our understanding of exoplanet atmospheres. We describe the EXCITE design and show results of analytic and numerical calculations of the instrument sensitivity. We show that an instrument like EXCITE will produce a wealth of quality data, both complementing and serving as a critical bridge between current and future space-based near infrared spectroscopic instruments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".