<scp>L</scp>ac‐<scp>M</scp>égantic accident: What we learned
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
A tragic train derailment in Lac‐Megantic, a small Quebec community caused 47 fatalities, the destruction of part of the town and huge cleaning costs. The Transportation Safety Board of Canada (TSB) has conducted an in‐depth investigation of the causes of Lac‐Mégantic accident and has formulated recommendations. The catastrophic consequences of the Lac‐Mégantic accident and the known increase over the last several years in rail transportation of Class 3 hazardous materials has made it clear, the need to review the existing regulations and industry practices to such transportation. Canada Transport Safety Board, U.S. National Transportation Safety Board, Transport Canada, U.S. Pipeline and Hazardous Material Safety Administration, and U.S. Federal Railroad Administration are working closely to upgrade rail transport regulations to prevent similar incidents from occurring. The tragedy in Lac‐Mégantic was not caused by one single person, action, or organization. Many factors played a role, and addressing the safety issues will take a concerted effort from regulators, railways, the Association of American Railroads, shippers, tank car manufacturers, and refiners in Canada and the United States. © 2014 American Institute of Chemical Engineers Process Saf Prog 34: 2–15, 2015
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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