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Classical Microdosimetry in Radiation Protection Dosimetry and Monitoring

2002· article· en· W1996097462 on OpenAlexaff
A.J. Waker, U.J. Schrewe, Jay Burmeister, J. Dubeau, R.A. Surette

Bibliographic record

VenueRadiation Protection Dosimetry · 2002
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsKermaDosimetryEquivalent dosePhysicsHealth physicsRadiation protectionMedical physicsDosimeterNuclear medicineNuclear engineeringComputational physicsNuclear physicsEngineeringMedicine

Abstract

fetched live from OpenAlex

Classical microdosimetry concerns the measurement and analysis of the spectrum of radiation energy deposition events in simulated microscopic tissue-equivalent sites. Over the past three decades, classical microdosimetry has been extensively applied for the direct measurement of dosimetric quantities, such as the ambient dose equivalent, and for the spectroscopic properties of tissue-equivalent proportional counters that have led to methods of mixed-field analysis and particle identification. This paper reviews some of the special applications of classical microdosimetry such as the determination of kerma coefficients, differential dosimetry and aviation dosimetry. Also reviewed are some of the technological innovations related to the application of microdosimetry in operational health physics and in particular the development of multi-element proportional counters and detectors based on gas microstrip technology.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.006
Science and technology studies0.0010.005
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.003

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 head0.029
GPT teacher head0.263
Teacher spread0.234 · 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 designTheoretical or conceptual
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

Citations8
Published2002
Admission routes1
Has abstractyes

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