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Record W2165719330 · doi:10.1093/rpd/nci024

Aircrew dosimetry using the predictive code for aircrew radiation exposure (PCAIRE)

2005· article· en· W2165719330 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 · 2005
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsAircrewDosimetryEnvironmental scienceCosmic rayMeteorologyAltitude (triangle)RadiationPhysicsNeutronAeronauticsAerospace engineeringNuclear medicineNuclear physicsEngineeringMedicineMathematics

Abstract

fetched live from OpenAlex

During 2003, a portable instrument suite was used to conduct cosmic radiation measurements on 49 jet-altitude flights, which brings the total number of in-flight measurements by this research group to over 160 flights since 1999. From previous measurements, correlations have been developed to allow for the interpolation of the dose-equivalent rate for any global position, altitude and date. The result was a Predictive Code for Aircrew Radiation Exposure (PCAIRE), which has since been improved. This version of the PCAIRE has been validated against the integral route dose measurements made at commercial aircraft altitudes during the 49 flights. On most flights, the code gave predictions that agreed to the measured data (within +/- 25%), providing confidence in the use of PCAIRE to predict aircrew exposure to galactic cosmic radiation. An empirical correlation, based on ground-level neutron monitoring data, has also been developed for the estimation of aircrew exposure from solar energetic particle (SEP) events. This model has been used to determine the significance of SEP exposure on a theoretical jet altitude flight during GLE 42.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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