StEER: Hurricane Melissa Annotated Media Repository , in StEER - 28 October 2025 Hurricane Melissa
Bibliographic record
Abstract
Since 1912, Jamaica has experienced six major hurricanes, striking on average every 23 years and repeatedly disrupting communities, infrastructure, and the economy. The latest among these is Hurricane Melissa which made landfall October 28, 2025 on Jamaica’s southwestern coast near New Hope in Westmoreland Parish at 1:00 PM EDT (17:00 UTC). The storm made landfall as a Category 5 hurricane with estimated maximum sustained winds of 185 mph (295 km/h) and an estimated minimum central pressure of 892 mb, placing it among the most intense storms on record in the Atlantic basin. After crossing Jamaica from southwest to northeast, Melissa made a second landfall in eastern Cuba as a Category 3 storm, while also impacting parts of Haiti. In response, StEER activated a Level 1 response to evaluate Hurricane Melissa with a Virtual Assessment Structural Team (VAST) formed on October 28, 2025. The VAST was tasked with producing the primary product of this Level 1 response: this Preliminary Virtual Reconnaissance Report (PVRR) and accompanying Media Repository (this file). This annotated media repository is a supplement to StEER for the Hurricane Melissa Preliminary Virtual Reconnaissance Report (PVRR). The repository is a visual catalog of geolocated photographic evidence, organized by different hazard and structural classes, and annotated with team member interpretations and analyses.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.382 | 0.168 |
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".