Scheduling Ocean Color Observations for a GEO-Stationary Satellite
Bibliographic record
Abstract
The GEO-Stationary Coastal and Air Pollution Events (GEO-CAPE) mission plans to put a visible spectrum imaging instrument on a satellite in geo-stationary orbit to perform ocean color remote sensing. Two different instrument designs, Filter Radiometer (FR) and COastal Ecosystems Dynamic Imager (COEDI), with different shape for the imaged area and image acquisition time, are being evaluated. Scheduling observations for either instrument requires optimizing science objectives in the presence of predicted cloud cover and available daylight. We model this scheduling problem as both Mixed Integer Linear Program (MILP) and Constraint Programming (CP) problems, and compare these two formulations for FR and COEDI using real cloudiness data collected at different times throughout the year. Our results show that MILP is the more suitable technique, and the schedule quality metric shows FR is the preferred design. We have reported our results to the GEO-CAPE mission team to assist them making an informed decision for the next step in formulating this mission.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".