New York State's Inland Geographic Response Plans
Bibliographic record
Abstract
Geographic Response Plans (GRPs) are location-specific plans developed to provide guidance for oil spill responses throughout the United States. Until recently, the majority of crude oil transportation in the United States has occurred via waterways on oil tankers and barges, therefore, most existing GRPs focus on the protection of sensitive biological resources and socio-economic features in near shore environments. The recent development of crude oil extraction from the Bakken formation has resulted in a significant increase in the volume of crude oil being transported via railroads and pipelines and has highlighted the need for inland response planning. Rail cars transporting the volatile and flammable Bakken crude oil now traverse more than 850 miles of New York State on two major Class 1 Railroads. In response, Executive Order 125 was issued by the governor directing state agencies to strengthen the state's preparedness for incidents involving crude oil transportation. New York State's (NYS) Department of Environmental Conservation (DEC), in collaboration with the Department of Homeland Security & Emergency Services and Department of Health, are leading a multi-stakeholder effort to develop Inland GRPs for the 21 NYS counties currently impacted by crude-by-rail transportation. County steering committees were established consisting primarily of local first response agencies, as well as their state and federal partners. Utilizing Sensitive Resource Maps developed by DEC, coupled with the local steering committee input, location-specific response plans were drafted, reviewed, and set as final working “evergreen” documents, which are open for update/refinement at any time in the future. The NYSDEC GRPs are similar to typical GRPs in that they are map-based, location-specific contingency plans that outline response strategies for the protection of sensitive resources. However, the NYSDEC GRPs differ from traditional GRPs in several ways. They extend contingency planning to cover spills on land, in addition to surface water-based spills. Due to the flammability of Bakken crude oil, much more emphasis is placed on the fire risks associated with a train derailment. This is done by mapping sensitive human receptors (e.g., schools, daycare centers, assisted living centers, etc.), critical infrastructure, and identifying fire (and vapor) suppression assets. The NYSDEC GRPs also place more emphasis on the initial response options available to local first responders, options that can be implemented before other response assets may arrive on-scene (State, Federal, and RP). This presentation will discuss the development, structure, proposed implementation, training and exercises associated with this ongoing program.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.133 | 0.036 |
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".