Bibliographic record
Abstract
A public/private collaboration between federal, state, provincial, and local U.S. and Canadian governmental organizations, called the Canada - United States Cargo Security Project has been formed, with the goal to improve security of containerized cargo moving from overseas locations into eastern Canadian provinces and the Northeastern United States. The current phase of this project has two technical objectives. These are: (1) to build and test a prototype in-container sensor system able to detect unauthorized entry into the container and the presence of radioactive material, to record geographical location and environmental data, and to transmit this information via satellite communications to a remote monitoring facility, and (2) to develop a secure website where data from the in-container sensors and other information will be displayed in real or near-real time and can be made available to law enforcement and emergency response organizations as appropriate. This paper will describe these activities, currently being undertaken by the Lawrence Livermore National Laboratory. An additional goal of the project's current phase is to integrate multi-jurisdictional training and first-responder exercises while monitoring and tracking container shipments from overseas to the US via Canadian ports-of-entry into North America. This activity is being undertaken by other project partners, which include the National Infrastructure Institute--Center for Infrastructure Expertise (NI2CIE), Transport Canada, Canadian Provinces of Quebec and Nova Scotia, Ports of Halifax and Montreal, U.S. Coast Guard (First Coast Guard District), States of New Hampshire, Maine, Vermont, and New York and the Port of Portland.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.005 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".