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Record W2329353178 · doi:10.1097/hp.0b013e318217fb48

REVISED REQUIREMENTS FOR RADIATION EMERGENCY BIOASSAY TECHNIQUES FOR THE PUBLIC AND FIRST RESPONDERS

2011· article· en· W2329353178 on OpenAlexaff
Chunsheng Li, Gary H. Kramer

Bibliographic record

VenueHealth Physics · 2011
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsRadiological weaponBioassayRadioactive contaminationMedicinePopulationRadiation doseMedical physicsRadiation protectionEffective dose (radiation)Radiation exposureEnvironmental healthMedical emergencyContaminationNuclear medicineBiologySurgery

Abstract

fetched live from OpenAlex

This technical note reports the required sensitivities for bioassay techniques derived from a 0.1 Sv effective dose incurred in the first year following an emergency (recommended by ICRP) and those derived from a 0.25 Sv committed effective dose (recommended by NCRP) as dose thresholds for possible medical attention. During a large-scale radiological or nuclear emergency, the dose threshold chosen for medical attention may be raised, as available resources may be insufficient for conducting a sensitive contamination assessment and medical treatment of a large population exposed to radioactive contamination.

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)0.039
metaresearch head score (Gemma)0.072
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.039
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.072
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0060.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0090.014

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 head0.158
GPT teacher head0.389
Teacher spread0.230 · 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
GenreMethods

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

Citations13
Published2011
Admission routes1
Has abstractyes

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