RT Dataset -- Updated radiative transfer model for Titan in the near-infrared wavelength range: Validation against Huygens atmospheric and surface measurements and application to the Cassini/VIMS observations of the Dragonfly landing area
Bibliographic record
Abstract
This dataset contains all Radiative Transfer (RT) results made for the paper. The data are stored in 4 zipped-folders names with the VIMS cube flyby and id: TB_C1481624349_1 T40_C1578266417_1 T38_C1575509158_1 T40_C1578263500_1 T40_C1578263152_1 The HLS folder contains the VIMS cubes, the HLS end-member (End_member.txt), and the corresponding surface albedo (Surface_albedo.txt). In these folders, each VIMS pixel is stored in a .txt file with the following pattern: _ _ .txt It starts with a header describing the observation: CUBE_ID: the VIMS cube id (`C1234567890_1` format) SAMPLE: the pixel sample number. LINE: the pixel line number. LONG: the pixel longitude (in degree). LAT: the pixel latitude (in degree). INC: the surface incident angle (in degree). EMI: the surface emergent angle (in degree). PHASE: the surface phase angle (in degree). For the Selk crater cubes (T40_C1578266417_1, T38_C1575509158_1, T40_C1578263500_1, T40_C1578263152_1), the header also contains the spatial sampling and the radiative transfer model outputs: Spatial sampling (km/pix). Fh: the haze scaling factor. Fm: the mist scaling factor. 1-sigma (Fh): the 1-sigma uncertainty on Fh. 1-sigma (Fm): the 1-sigma uncertainty on Fm. Reduced chi2: the reduced chi2. Then contains the observed spectra: Column 1: the VIMS channel central wavelength (in micrometers). Column 2: the VIMS pixel I/F. Column 3: the VIMS pixel I/F 1-sigma uncertainty. For the Selk crater cubes (T40_C1578266417_1, T38_C1575509158_1, T40_C1578263500_1, T40_C1578263152_1), 3 columns are added for: Column 4: the surface albedo. Column 5: the upper 1-sigma uncertainty on the surface albedo. Column 6 : the lower 1-sigma uncertainty on the surface albedo.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.022 |
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".