Infrared Study of Hydrocarbons Mixtures Under Titan Simulated Conditions
Bibliographic record
Abstract
Introduction Titan is the only body other than Earth in our Solar System with thick atmosphere and surface liquid. It has been suggested that Titan has an active hydrological cycle expressed at the surface by the presence of lakes and seas [1]. The average surface temperature is 94K which allows methane and ethane to be liquid on Titan. Photodissociation of the methane in the upper atmosphere produces several other hydrocarbons such as propane, hydrogen cyanide, butane, acetylene, etc... [2]. The Cassini Visual and Infrared Mapping Spectrometer (VIMS) have obtained spectral data over Ontario Lacus displaying a possible absorption feature at 2 μm interpreted as liquid ethane inside the lake [3]. Other possible absorption feature at 5 μm, attributed to various hydrocarbons or nitriles along the margin of Ontario Lacus [4]. The detection of the other compounds in lakes remains challenging, due to the presence of methane in the atmosphere, which absorbs all the solar radiation except at few wavelengths known as atmospheric windows. Several hydrocarbons exist as solids and can be dissolved in liquids and/or cover Titan’s surface [2], but Infrared reflectance spectra acquired in Titan’s surface conditions would allow their potential detection using VIMS data, are often lacking. We investigated several hydrocarbons to characterize the infrared properties of Titan’s liquids and ices. Spectra are then quantitatively analyzed and used to show the presence/absence of these compounds during evaporation/sublimation processes
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".