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Record W2329253745 · doi:10.1097/hp.0b013e3182499477

Results and Lessons Learned from Radiological/Nuclear Emergency Response Exercise Held in Québec, Canada

2012· article· en· W2329253745 on OpenAlexaffabout
Dominic Lortie, Sonia Johnson, Nadereh St-Amant, Dominic Larivière, Germain Tremblay, Danielle Richoz, Christophe Romiguière, Etienne Frenette, Jason M. Brown

Bibliographic record

VenueHealth Physics · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsCanadian Nuclear Safety CommissionDepartment of National DefenceDefence Research and Development CanadaHealth CanadaUniversité Laval
Fundersnot available
KeywordsChristian ministryEmergency responseRadiological weaponNuclear powerEnvironmental sciencePolitical scienceMedical emergencyMedicinePhysicsNuclear physics

Abstract

fetched live from OpenAlex

The Ministry of Sustainable Development, Environment and Parks of Québec (Ministère du Développement durable, de l'Environnement et des Parcs du Québec-MDDEP) held a 3-d provincial nuclear emergency response exercise in September 2008 that saw participation from Canadian provincial and federal departments. Nuclear emergency exercises are regularly held in Québec, given the presence of the Gentilly-2 nuclear power plant situated in Bécancour on the St. Lawrence River. The significance of this exercise is that it marks the first exercise held in Canada where environmental samples spiked with relevant radioisotopes were analyzed during the exercise, both on-site and remotely, and where the results of those analyses had a direct impact on the decisions made during the exercise. Following the exercise, samples were sent to two other laboratories that are part of the Canadian National Nuclear Laboratory Network for analysis, providing the first intercomparison exercise for the Network. The results of the analysis of the air and drinking water samples, as well as the lessons learned during the exercise, are presented and discussed in this article.

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 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)0.000
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 score0.695
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.051
GPT teacher head0.294
Teacher spread0.243 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2012
Admission routes2
Has abstractyes

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