Historical background: early deliberations on and assessments of need for dynamic crush test
Bibliographic record
Abstract
Beginning in the late 1970s, discussions were fostered by the International Atomic Energy Agency (IAEA) on the need for additional tests for some type B packages. Consideration at the international level of these early deliberations and tests ultimately led to the inclusion in the IAEA Regulations for the Safe Transport of Radioactive Material of the third mechanical (drop) test for demonstrating the ability of the package design to withstand accident conditions of transport, commonly known as the ‘dynamic crush test’. This test included the requirement that the package be positioned so as to sustain maximum damage. Recently discussions have been occurring as to what constitutes positioning on an unyielding target, where considerations are being put forward for clarifying this phrasing and possibly changing the test requirement. Some of these proposed changes could make the test more demanding than originally envisioned. This paper, developed in support of a panel discussion at PATRAM 2010, provides an overview of some of the very early thinking behind the crush test. It includes a graphic demonstration that was used at the time to demonstrate the concerns that then existed. It also provides a brief review of the results of various tests performed in the US, UK and Canada from the mid-1960s through the early 1980s.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".