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
Three recent accidents involving the release of hazardous material have focused attention on the structural integrity of railroad tank cars: (1) Minot, ND, on January 18, 2002; (2) Macdona, TX, on June 28, 2004; and (3) Graniteville, SC, on January 6, 2005. Each of these accidents resulted in fatalities. Research is being conducted to develop strategies for improving railroad tank cars so they can maintain tank integrity in severe accidents. A collaborative effort called the Next Generation Rail Tank Car (NGRTC) Project intends to use these research results to help develop improved tank car designs. Dow Chemical Company, Union Pacific Railroad, and Union Tank Car Company are the industry sponsors of the NGRTC Project. The Federal Railroad Administration (FRA) and Transport Canada participate in the NGRTC project through Memoranda of Cooperation. FRA and the Pipeline and Hazardous Materials Safety Administration intend to use these research results to support rulemaking. The approach taken in performing this research is to define the collision conditions of concern, to evaluate the behavior of current design equipment in these scenarios, and to develop alternative strategies for increasing the maximum impact speed for which tank integrity is maintained. The accident scenarios have been developed from a review of accidents and are intended to bound the range of main-line accidents that can lead to a release of hazardous material from a tank car. The accident scenarios and collision modes have been used to define car-to-car impact scenarios. These car-to-car impact scenarios define the conditions under which the commodity must be contained. The impact scenarios are being used to evaluate the integrity of current design and improved design tank cars. Full-scale impact tests are also being conducted, to help validate modeling of the baseline equipment. The models have been refined based on the test results. The models are now being applied to develop the improved equipment designs. This paper describes the overall research framework and provides an overview of the research done to date, as well as the planned efforts.
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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 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 it