Testing INCUS Methods Experiment – Suborbital preLaunch Investigation of Convective Evolution (TIME-SLICE)
Bibliographic record
Abstract
The upcoming NASA Earth Venture Mission Mission INvestigation of Convective UpdraftS (INCUS) seeks to estimate convective mass flux over the Earth's tropical regions using a unique new reflectivity differencing technique. Therefore, validation of the INCUS products requires innovative designs for time-resolved observations of convective cores from the surface. The Testing of INCUS Measurements Experiment - Suborbital preLaunch Investigation of Convective Evolution (TIME-SLICE) is a small campaign to understand and test instruments and sampling techniques that will provide the most useful validation of INCUS products. TIME-SLICE outcomes will directly influence the development and design of the post-launch validation effort for INUCS. This presentation will focus on the Colorado component of TIME-SLICE (TIME-SLICE CO), which took place in the northern front range of Colorado during the spring of 2024 (Fig. 1). The CSU CHIVO C-band polarimetric radar collected rapid vertical slices (RHIs) of convective cores identified and tracked by the Multi-Sensor Agile Adaptive Sampling (MAAS) framework. Several profiling radars, including the S-band Snow-level Radar (SLR) and a Micro Rain Radar Pro (MRR Pro), were installed about 30 km from CHIVO to provide vertical profiles of reflectivity and Doppler velocity. Surface rainfall characteristics and amounts were collected using disdrometers and rain gauges, and special soundings were launched to characterized the atmospheric environment of the storms sampled. During the approximately eight weeks of operations, thirteen intensive operation periods (IOPs) sampled a variety of convection, from shallow to deep, fast and slow moving, weak to severe. Preliminary examination of several IOPs, as well as key lessons learned for future INCUS field campaigns will be presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".