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Record W2121325380 · doi:10.1093/rpd/nch333

Assessment of aircrew radiation exposure by further measurements and model development

2004· article· en· W2121325380 on OpenAlexaff
B.J. Lewis

Bibliographic record

VenueRadiation Protection Dosimetry · 2004
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsRoyal Military College of Canada
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsAircrewEnvironmental scienceRadiationRadiation exposureMeteorologyAeronauticsNuclear medicineMedicinePhysicsOpticsEngineering

Abstract

fetched live from OpenAlex

A methodology is presented for collecting and analysing exposure measurements from galactic cosmic radiation using a portable equipment suite and encapsulating these data into a semi-empirical model/Predictive Code for Aircrew Radiation Exposure (PCAIRE) for the assessment of aircrew radiation exposure on any flight over the solar cycle. The PCAIRE code has been validated against integral route dose measurements at commercial aircraft altitudes during experimental flights made by various research groups over the past 5 y with code predictions typically within +/-20% of the measured data. An empirical correlation, based on ground-level neutron monitoring data, is detailed further for estimation of aircrew exposure from solar particle events. The semi-empirical models have been applied to predict the annual and career exposure of a flight crew member using actual flight roster data, accounting for contributions from galactic radiation and several solar energetic-particle events over the period 1973-2002.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.286
Teacher spread0.263 · 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 designSimulation or modeling
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

Citations43
Published2004
Admission routes1
Has abstractyes

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