MétaCan
Menu
Back to cohort
Record W2005348677 · doi:10.1093/rpd/ncq281

Hospital response for children as a vulnerable population in radiological/nuclear incidents

2010· article· en· W2005348677 on OpenAlex

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.

Bibliographic record

VenueRadiation Protection Dosimetry · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsKingston General Hospital
Fundersnot available
KeywordsTriageRadiological weaponPreparednessMedical emergencyPopulationEvent (particle physics)Emergency responseHealth careHazardous wasteOperations managementDisaster planningPersonal protective equipmentMedicineBusinessRisk analysis (engineering)Environmental healthEngineeringPoison controlDiseaseHuman factors and ergonomicsPolitical scienceCoronavirus disease 2019 (COVID-19)Waste managementSurgery

Abstract

fetched live from OpenAlex

Emergency planning in the healthcare industry is a relatively new field. Planning for radiological and nuclear (R/N) events is even newer. Consequently, the amount of training and education that has been produced and conducted, thus far, has been minimal when compared with other fields in healthcare. To compound this issue, the planning and research that have been completed has, without a doubt, been focused on adults. Children represent a significant portion of the population. They would, unquestionably, be affected by any large-scale R/N event and have been, for the most part, ignored in planning processes. Identified gaps in the planning and preparedness process should provide the basis for moving forward and putting protocols in place for dealing with children during these types of incidents. Gaps can be summarised into categories, or stages of reaction to an R/N event. These categories include: mitigation and planning processes; triage or incident response issues and recovery procedures following the initial response. The primary goals of the hospital in a hazardous event are to: In order to achieve the above goals, hospitals must have procedural response plans, personal protective equipment (PPE), decontamination equipment and training to ensure knowledge and implementation for an effective response. Figure 1 provides a framework for hospital decontamination planning.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.009
GPT teacher head0.292
Teacher spread0.283 · 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