MétaCan
Menu
Back to cohort

Radiological Emergency Response: The National Biological Dosimetry Response Plan

2007· article· en· W2112408182 on OpenAlexafffund
J.-A. Dolling, Douglas R. Boreham

Bibliographic record

VenueDose-Response · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsMcMaster UniversityCredit Valley Hospital
FundersHealth CanadaAtomic Energy of Canada Limited
KeywordsDosimetryRadiological weaponMedical physicsPresentation (obstetrics)MedicineRisk analysis (engineering)Medical emergencyNuclear medicine

Abstract

fetched live from OpenAlex

This presentation will discuss new developments in emergency biological dosimetry and the CRTI (CBRN Research and Technology Initiative) National Biological Dosimetry Response Plan (NBDRP). Biological dosimetry is a technique used to estimate the biological consequences of a radiation exposure and is largely based on chromosome aberration detection. The NBDRP will establish a national network of laboratories to respond to a nuclear event for the purposes of rapid radiation dose estimation for crisis management and for long-term health risk assessment. In the event of a large-scale radiation accident or deliberate act of terrorism this will help guide the actions of emergency officials, emergency responders and health care personnel by providing timely biological dose estimates. The presentation will outline the research initiatives to develop modern techniques used for biological dosimetry. The overall purpose of this presentation is to provide the audience with a brief introduction to radiobiology, radiation-induced DNA damage, the health risks associated with radiation exposure, and the latest cytogenetic techniques used to estimate the risk.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0250.015

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 head0.041
GPT teacher head0.331
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueDose-ResponseSame topicCarcinogens and Genotoxicity AssessmentFrench-language works237,207