HETEAC – The Hybrid End-To-End Aerosol Classification model for EarthCARE: Look-Up Table (LUT) for aerosol mixtures
Bibliographic record
Abstract
The dataset contains the look-up table (LUT) of EarthCARE’s Hybrid End-To-End Aerosol Classification (HETEAC) model. The LUT contains optical and radiative parameters for four pure aerosol components (fine mode weakly absorbing, fine mode strongly absorbing, coarse mode spherical and coarse mode non-spherical) and their mixtures. In total, 314 aerosol mixtures are considered. The LUT returns the mixing state of an aerosol mixture based on the lidar ratio and the particle linear depolarization ratio at 355 nm. The mixing state is expressed in terms of relative volume contribution of the four pure aerosol components. Additionally, the LUT returns the effective radius, the asymmetry parameter, the single scattering albedo (at 355, 532, 550, 670, 865, 1064, 1650 and 2210 nm) and the Angstrom exponent (at 28 wavelength combinations) of the aerosol mixture. The lidar ratio and the particle linear depolarization ratio is also provided at 532, 550, 670, 865, 1064, 1650 and 2210 nm. The datafile contains two top-level groups: the HeaderData, which contains the header variables, and the ScienceData with the variables. The latter contains two groups, the AerosolComponents, which includes the aerosol-component-related optical and microphysical variables, and the LookUpTable, which contains the HETEAC LUT variables. The variables included in the datafile are listed below. For each variable, a full description is provided in the long_name attribute. HeaderData angstrom_exponent_header ScienceData AerosolComponents backscatter effective_radius extinction logarithmic_width mode_radius_number mode_radius_volume particle_linear_depolarization_ratio refractive_index_imaginary refractive_index_real scattering LookUpTable angstrom_exponent asymmetry_parameter effective_radius lidar_ratio particle_linear_depolarization_ratio relative_volume_contribution single_scattering_albedo radiation_wavelength Contact For any further clarifications or expression of interest with respect to the EarthCARE LUT, please contact Ulla Wandinger (ulla.wandinger@tropos.de) and/or Athena Augusta Floutsi (floutsi@tropos.de).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.012 |
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; both teacher heads agree on what is shown here.
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".