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Exercise Maritime Response (EXMR): Lessons Learned for Population Monitoring and Communications

2007· article· en· W2029987409 on OpenAlex
Gary H. Kramer, Sonia Johnson, Barry M. Hauck, Kevin Capello, Debora Quayle

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Physics · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsHealth Canada
Fundersnot available
KeywordsEmergency responseTerrorismPopulationRadiological weaponAeronauticsRadioactive contaminationTest (biology)Medical emergencyEnvironmental healthEngineeringOperations managementPublic relationsBusinessMedicinePolitical scienceContamination

Abstract

fetched live from OpenAlex

Exercise Maritime Response was the third in a series of four emergency response exercises sponsored by the Chemical, Biological, Radiological and Nuclear Research and Technology Initiative. It was designed to test the Canadian Federal, Provincial and Municipal response to a terrorist attack using radioactive materials. The complexity of this exercise had been increased over previous exercises to now include simulated contaminated members of the public. This paper summarizes the experiences, and the lessons learned, of the Health Canada (HC) team. The largest issues identified by the HC team were: crowd control, insufficiency of staff to deal with surge capacity, and communications. The exercise did prove that the population monitoring equipment worked well and that small amounts of radioactivity were easily identified and quantified to within 20% of their true value.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.081
GPT teacher head0.391
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it