Development of a Global Oil Spill Modeling System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper describes the development of an oil spill modeling system that is operational on a global scale and can be used for both real-time response, forecast simulations and probabilistic risk analysis based on climatological wind and ocean current data. For ocean and estuarine spills, the system makes use of the General NOAA Operational Modeling Environment (GNOME) oil spill model, Trajectory Analysis Planner and the Automated Data Inquiry for Oil Spills weathering model. Hydrodynamic and meteorological data is obtained from the US Navy and National Oceanic and Atmospheric Administration. Data access is provided through the Naval Oceanographic Office, the Fleet Numerical Meteorological and Oceanographic Center and the GNOME Online Oceanographic Data Server. For riverine spills, the GeoSpatial Stream Flow Model and the Incident Command Tool for Drinking Water Protection are used to respectively, build river networks with associated flows and velocities and, transport and disperse oil spill contamination downstream. Case study examples are presented for both forecast simulations and probabilistic risk analysis.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 it